OnlyDataJobs.com

Turnberry Solutions
  • Philadelphia, PA

TITLE:  Data Scientist

Years of Experience: 7+
Education Required: Bachelors Degree or Equivalent Work Experience

Interview Details:
- Phone Interview
- Face to Face Mandatory - Video Call is not an option


Purpose:
Looking for a Data Scientist who will support operations and data architecture teams with insights gained from analyzing company data. You must be that person who can create value out of data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. Such a person proactively fetches information from various sources and analyzes it for better understanding about how the business performs. Additionally, they can utilize AI tools to automate certain processes
 
This person must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. This Data Scientist must possess the skill-sets necessary to hit the ground running and must be willing to learn about the mobile phone business while solving problems quickly and efficiently.
 
See Yourself:

  • Working with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms to apply to data sets.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.

Position Requirements

Minimum Requirements:
  • Four-year degree in a related Computer Science, Math or Statistical field of study.
  • 7+ continuous years' of professional experience as a Data Scientist.
  • Strong problem solving skills with an emphasis on product development.
  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
  • Experience working with and creating data architectures.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • A drive to learn and master new technologies and techniques.
  • Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
  • SUPERB communication skills with an emphasis on writing and interpreting abilities
  • Excellent presentation skills. Must have the ability to confirm complex data into digestible formats for non-technical business teams.
Extended Requirements:
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • Experience using web services: Redshift, S3, Spark, etc.
  • Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
  • Experience analyzing data from 3rd party providers.
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
  • Experience visualizing/presenting data for stakeholders.
Physical Environment and Working Conditions:
Agile open floor plan
Onsite 5 days a week
ING
  • Amsterdam, Netherlands
ING is looking for experienced hires to help build on our Global Analytics ambition


About ING


Think Forward! Our purpose is to empower people to stay a step ahead in life and in business. We are an industry recognized strong brand with positive recognition from customers in many countries, a strong financial position, Omni-channel distribution strategy and international network. If you want to work at a place where we believe that you can make the difference by using machine learning to generate data driven products and solve the most pressing business challenges, please read on.


We are incredibly excited about Data Analytics and the great potential for progress and innovation. We believe that analytics is a key differentiator in bringing “anytime, anywhere, personalized” services to our customers.  We wish to improve our operational processes and create new and innovative data driven products that go beyond traditional banking, such as the platform models.  Achieving this vision will require us to build and expand on our analytics effort and organize ourselves around focused value buckets with strong coordination capabilities of data, technology, customer journey, UX, as well as external partnerships. 



Global Analytics


Global Analytics is a new unit responsible for realizing this vision for ING, differentiating ING as a leader in data-driven organization, within the banking sector and beyond. The team consists of a number of Global Analytics Center of Excellences around the bank’s key capabilities (such as Pricing, Risk Management, Financial Crime, Customer Intelligence, etc.) as well as strong coordination areas around data management, technology, customer journey, UX, as well as external partnerships.



Financial Crime & RegTech CoE (Center of Excellences)


To be a compliant and safe bank is non-negotiable precondition of everything we do. 


Purpose of the Financial Crime and RegTech center of excellence is to define the strategy and drive the development, implementation and adoption of analytics capabilities in the financial crime domain to make ING a safer and more compliant bank



Role Profile


As part of the center of excellence you will help creating innovative scalable data driven solutions in the space of Financial Crime. You proactively work with teams to implement these solutions across the organization.


You will work collaboratively with an extended group of stakeholders, including but not limited to Operations, Compliance, Engineering, Legal, Corporate Audit.


A background in anti-money laundering services or fraud is therefore a plus



About you



  • You Data Science knowledge enables you build analytics solutions for mitigation of Financial Crime related risks.

  • Willing and able to learn and to improve your technical as well your interpersonal skills.

  • You are a creative and curious Data Scientist who looking forward to work on a wide variety of Financial Economic Crime related problems.

  • You have a thorough understanding of the machine learning algorithms and tooling and are able to pass your knowledge to others.

  • Your are proficient in coding and you are able to deliver production ready code.

  • You have extensive experience with transforming data to added value for your stakeholders. You are able to see things from a different perspective and to make original solutions work in practice; when suitable you propose such endeavors to stakeholders.

  • You are able to see where ING can set further steps towards becoming a truly data driven bank. You’re always thinking one step ahead, for example in advising about the best way of implementation.

  • Your communication skills enable you to work together with many different parties throughout our organization.

  • You have extensive experience with stakeholder management from within data science projects.

  • Your enthusiasm is visible and you are good with mobilizing people for our data driven purpose.




  • You like working in cross-functional teams to realize an ambitious goal.

  • You are not shy to ask for help of other Data Scientists in the team, and you are happy help them out by sharing your knowledge and capabilities. You are able and willing to guide junior Data Scientists and interns in their work; you also have experience doing so in your previous roles.

  • You are a team player who strikes effective balance between independence and acting in the interest of the team.

  • You are perseverant and you do not give up when a problem is hard; you know how to deal with set-backs.

  • Your enthusiasm is contagious and inspires others to act; your act sets an example for others.


Candidate Profile



  • MSc or PhD with excellent academic results in the field of Computer Science, Mathematics, Engineering, Econometrics or similar.

  • At least 3/4 years work related experience in a similar role and/or environment.

  • Machine Learning: Classification, Regression, Clustering, Unsupervised methods, Text Mining. You have an excellent understanding of Random Forests, Gradient Boosting, Neural Networks, Logistic Regression, SVM, KNN, K-Means, etc. Parametric and non-parametric statistics is a pre.

  • Programming Languages: Python and R. Scala is a pre

  • Tools: Spark, Hadoop.

  • Database handling: SQL, Hive. Familiarity with Oracle, Netezza, HBase, Cassandra, Graph databases is a pre.

  • Visualisation tools: D3.js, Shiny, Angular.



Do you recognize a call upon You in our description? Then please apply and join us to change the future of banking!

TomTom
  • Amsterdam, Netherlands
At TomTom…

You’ll move the world forward. Every day, we create the most innovative mapping and location technologies to shape tomorrow’s mobility for the better.


We are proud to be one team of more than 5,000 unique, curious, passionate problem-solvers spread across the world. We bring out the best in each other. And together, we help the automotive industry, businesses, developers, drivers, citizens and cities move towards a safe, autonomous world that is free of congestion and emissions.

What you’ll do



  • Have a direct impact on our solutions for automated HD mapping, closely interacting with R&D engineers

  • Design, implement and extend our large-scale codebase in Python & TensorFlow, containing both prototyping and production code

  • Implement internal tools and services to make our machine learning solutions work in production



What you’ll need



  • Expert knowledge of Python

  • Hands-on experience with Cloud Computing (AWS, Azure), Microservices, Containers, CI/CD (Jenkins)

  • Experience with writing clean, elegant and maintainable production-level code

  • Ability to participate in the development and delivery cycle, from analysis, through implementation, to deployment and maintenance in production

  • Good understanding of mathematics, geometry, statistics, and software design principles



What’s nice to have



  • Experience with modern C++

  • Experience with deep learning frameworks, e.g., TensorFlow or PyTorch

  • High motivation for getting research products and prototypes into production

  • Being technically proactive, learning about new technologies, judging their value, and promoting their adoption when beneficial

  • Creative problem solver and team player; TomTom is a collaborative environment



Meet your team



We’re Autonomous Driving (AD). Our product unit develops, delivers and maintains products for advanced driver-assistance systems and automated driving – with the TomTom HD Map at the core of our work. Every day, we welcome new challenges, do world-class R&D and apply it using the latest machine learning and computer vision techniques. On our team, you’ll not only play a part in making autonomous driving a reality, you’ll transform the way people commute while boosting safety and comfort for everyone on the road.




Achieve more

We are self-starters who play well with others. Every day, we solve new problems with creativity, meet new people and learn rapidly at our offices around the world. We will invest in your growth and are committed to supporting you. In everything we do, we’re guided by six values: We care, putting our heart into what we do; we build trust (you can count on us); we create – driven to make a difference; we are confident, but don’t boast; we keep it simple, since life is complex enough; and we have fun because life’s too short to be boring. 

After you apply

Our recruitment team will work hard to give you a meaningful experience throughout the process, no matter the outcome. Your application will be screened closely and you can rest assured that all follow-up actions will be thorough, from assessments and interviews through your onboarding.

TomTom is an equal opportunity employer

We celebrate diversity, thrive on each other’s differences and are committed to creating an inclusive environment at our offices around the world. Naturally, we do not discriminate against any employee or job applicant because of race, religion, color, sexual orientation, gender, gender identity or expression, marital status, disability, national origin, genetics, or age.

Ready to move the world forward?

Freeport-McMoRan
  • Phoenix, AZ

Provide management and leadership to the Big Data project teams. Directs initiatives in the Freeport-McMoRan Big Data program. Provides analytical direction, expertise and support for the Big Data program; this includes project leadership for initiatives, coordination with business subject matter experts and travel to mine sites. This will be a global role that will coordinate with site and corporate stakeholders to ensure global alignment on service and project delivery. The role will also work with business operations management to ensure the program is focusing in areas most beneficial to the company.


  • Work closely with business, engineering and technology teams to develop solution to data-intensive business problems
  • Supervise internal and external science teams
  • Perform quality control of deliverables
  • Prepare reports and presentations, and communicate with Executives
  • Provide thought leadership in algorithmic and process innovations, and creativity in solving unconventional problems
  • Use statistical and programming tools such as R and Python to analyze data and develop machine-learning models
  • Perform other duties as required


Minimum Qualifications


  • Bachelors degree in an analytical field (statistics, mathematics, etc.) and eight (8) years of relevant work experience, OR
  • Masters degree in an analytical field (statistics, mathematics, etc.) and six (6) years of relevant work experience, OR
  • Proven track record of collaborating with business partners to translate business problems and needs into data-based analytical solutions
  • Proficient in predictive modeling:
  • Linear and logistic regression
  • Tree based techniques (CART, Random Forest, Gradient Boosting)
  • Time-Series Analysis
  • Anomaly detection
  • Survival Analysis
  • Strong Experience with SQL/Hive environments
  • Skilled with R and/or Python analysis environments
  • Experience with Big Data tools for machine learning, R, Hive, Python
  • Good communication skills


Preferred Qualifications


  • Doctorate degree in an analytical field
  • Willing and able to travel 20-30% or more


Criteria/Conditions


  • Ability to understand and apply verbal and written work and safety-related instructions and procedures given in English
  • Ability to communicate in English with respect to job assignments, job procedures, and applicable safety standards
  • Must be able to work in a potentially stressful environment
  • Position is in busy, non-smoking office located in downtown Phoenix, AZ
  • Location requires mobility in an office environment; each floor is accessible by elevator
  • Occasionally work will be performed in a mine, outdoor or manufacturing plant setting
  • Must be able to frequently sit, stand and walk
  • Must be able to frequently lift and carry up to ten (10) pounds
  • Personal protective equipment is required when performing work in a mine, outdoor, manufacturing or plant environment, including hard hat, hearing protection, safety glasses, safety footwear, and as needed, respirator, rubber steel-toe boots, protective clothing, gloves and any other protective equipment as required
  • Freeport-McMoRan promotes a drug/alcohol-free work environment through the use of mandatory pre-employment drug testing and on-going random drug testing as allowed by applicable State laws


Freeport-McMoRan has reviewed the jobs at its various office and operating sites and determined that many of these jobs require employees to perform essential job functions that pose a direct threat to the safety or health of the employees performing these tasks or others. Accordingly, the Company has designated the following positions as safety-sensitive:


  • Site-based positions, or positions which require unescorted access to site-based operational areas, which are held by employees who are required to receive MSHA, OSHA, DOT, HAZWOPER and/or Hazard Recognition Training; or
  • Positions which are held by employees who operate equipment, machinery or motor vehicles in furtherance of performing the essential functions of their job duties, including operating motor vehicles while on Company business or travel (for this purpose motor vehicles includes Company owned or leased motor vehicles and personal motor vehicles used by employees in furtherance of Company business or while on Company travel); or
  • Positions which Freeport-McMoRan has designated as safety sensitive positions in the applicable job or position description and which upon further review continue to be designated as safety-sensitive based on an individualized assessment of the actual duties performed by a specifically identified employee.


Equal Opportunity Employer/Protected Veteran/Disability


Requisition ID
1900606 

Freeport-McMoRan
  • Phoenix, AZ

Supports the activities for all Freeport-McMoRan Big Data programs. Provides analytical support and expertise for the Big Data program; this includes coordination with business subject matter experts and travel to mine sites. The role will provide analyses and statistical models as part of Big Data projects, and may be the project lead on analytics initiatives. The role will also provide visualizations and descriptive results of the analysis. This will be a global role that will coordinate with site and corporate stakeholders to ensure alignment on project delivery.


    Work
    • closely with business, engineering and technology teams to analyze data-intensive business problems.
    • Research and develop appropriate statistical methodology to translate these business problems into analytics solutions
    • Perform quality control of deliverables
    • Develop visualizations of results and prepare deliverable reports and presentations, and communicate with business partners
    • Provide thought leadership in algorithmic and process innovations, and creativity in solving unconventional problems
    • Develop, implement and maintain analytical solutions in the Big Data environment
    • Work with onshore and offshore resources to implement and maintain analytical solutions
    • Perform variable selection and other standard modeling tasks
    • Produce model performance metrics
    • Use statistical and programming tools such as R and Python to analyze data and develop machine-learning models
    • Perform other duties as requested


Minimum Qualifications


  • Bachelors degree in an analytical field (statistics, mathematics, etc.) and five (5) years of relevant work experience, OR 
  • Masters degree in an analytical field (statistics, mathematics, etc.) and three (3) years of relevant work experience

  • Proven track record of collaborating with business partners to translate operational problems and needs into data-based analytical solutions

  • Proficient in predictive modeling:

  • Linear and logistic regression

  • Tree based techniques (CART, Random Forest, Gradient Boosting)

  • Time-Series Analysis

  • Anomaly detection

  • Survival Analysis

  • Strong experience with SQL/Hive environments

  • Skilled with R and/or Python analysis environments

  • Experience with Big Data tools for machine learning, R, Hive, Python

  • Good communication skills


Preferred Qualifications


  • Masters degree in an analytical field
  • Willing and able to travel 20-30% or more


Criteria/Conditions


  • Ability to understand and apply verbal and written work and safety-related instructions and procedures given in English
  • Ability to communicate in English with respect to job assignments, job procedures, and applicable safety standards

  • Must be able to work in a potentially stressful environment

  • Position is in busy, non-smoking office located in Phoenix, AZ

  • Location requires mobility in an office environment; each floor is accessible by elevator and internal staircase

  • Occasionally work may be performed in a mine, outdoor or manufacturing plant setting

  • Must be able to frequently sit, stand and walk

  • Must be able to frequently lift and carry up to ten (10) pounds

  • Personal protective equipment is required when performing work in a mine, outdoor, manufacturing or plant environment, including hard hat, hearing protection, safety glasses, safety footwear, and as needed, respirator, rubber steel-toe boots, protective clothing, gloves and any other protective equipment as required

  • Freeport-McMoRan promotes a drug/alcohol free work environment through the use of mandatory pre-employment drug testing and on-going random drug testing as per applicable State Laws


Freeport-McMoRan has reviewed the jobs at its various office and operating sites and determined that many of these jobs require employees to perform essential job functions that pose a direct threat to the safety or health of the employees performing these tasks or others. Accordingly, the Company has designated the following positions as safety-sensitive:


  • Site-based positions, or positions which require unescorted access to site-based operational areas, which are held by employees who are required to receive MSHA, OSHA, DOT, HAZWOPER and/or Hazard Recognition Training; or
  • Positions which are held by employees who operate equipment, machinery or motor vehicles in furtherance of performing the essential functions of their job duties, including operating motor vehicles while on Company business or travel (for this purpose motor vehicles includes Company owned or leased motor vehicles and personal motor vehicles used by employees in furtherance of Company business or while on Company travel); or
  • Positions which Freeport-McMoRan has designated as safety sensitive positions in the applicable job or position description and which upon further review continue to be designated as safety-sensitive based on an individualized assessment of the actual duties performed by a specifically identified employee.


Equal Opportunity Employer/Protected Veteran/Disability


Requisition ID
1900604 

FCA Fiat Chrysler Automobiles
  • Detroit, MI

Fiat Chrysler Automobiles is looking to fill the full-time position of a Data Scientist. This position is responsible for delivering insights to the commercial functions in which FCA operates.


The Data Scientist is a role in the Business Analytics & Data Services (BA) department and reports through the CIO. They will play a pivotal role in the planning, execution  and delivery of data science and machine learning-based projects. The bulk of the work with be in areas of data exploration and preparation, data collection and integration, machine learning (ML) and statistical modelling and data pipe-lining and deployment.

The newly hired data scientist will be a key interface between the ICT Sales & Marketing team, the Business and the BA team. Candidates need to be very much self-driven, curious and creative.

Primary Responsibilities:

    • Problem Analysis and Project Management:
      • Guide and inspire the organization about the business potential and strategy of artificial intelligence (AI)/data science
      • Identify data-driven/ML business opportunities
      • Collaborate across the business to understand IT and business constraints
      • Prioritize, scope and manage data science projects and the corresponding key performance indicators (KPIs) for success
    • Data Exploration and Preparation:
      • Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA)
      • Generate and test hypotheses about the underlying mechanics of the business process.
      • Network with domain experts to better understand the business mechanics that generated the data.
    • Data Collection and Integration:
      • Understand new data sources and process pipelines. Catalog and document their use in solving business problems.
      • Create data pipelines and assets the enable more efficiency and repeatability of data science activities.
    • Data Exploration and Preparation:
      • Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA)
    • Machine Learning and Statistical Modelling:
      • Apply various ML and advanced analytics techniques to perform classification or prediction tasks
      • Integrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction, sales, marketing
      • Testing of ML models, such as cross-validation, A/B testing, bias and fairness
    • Operationalization:
      • Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options
      • (Help to) integrate model performance management tools into the current business infrastructure
      • (Help to) implement champion/challenger test (A/B tests) on production systems
      • Continuously monitor execution and health of production ML models
      • Establish best practices around ML production infrastructure
    • Other Responsibilities:
      • Train other business and IT staff on basic data science principles and techniques
      • Train peers on specialist data science topics
      • Promote collaboration with the data science COE within the organization.

Basic Qualifications:

    • A bachelors  in computer science, data science, operations research, statistics, applied mathematics, or a related quantitative field [or equivalent work experience such as, economics, engineering and physics] is required. Alternate experience and education in equivalent areas such as economics, engineering or physics, is acceptable. Experience in more than one area is strongly preferred.
    • Candidates should have three to six years of relevant project experience in successfully launching, planning, executing] data science projects. Preferably in the domains of automotive or customer behavior prediction.
    • Coding knowledge and experience in several languages: for example, R, Python, SQL, Java, C++, etc.
    • Experience of working across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service, and others.
    • Experience with distributed data/computing and database tools: MapReduce, Hadoop, Hive, Kafka, MySQL, Postgres, DB2 or Greenplum, etc.
    • All candidates must be self-driven, curious and creative.
    • They must demonstrate the ability to work in diverse, cross-functional teams.
    • Should be confident, energetic self-starters, with strong moderation and communication skills.

Preferred Qualifications:

    • A master's degree or PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent.
    • Experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
    • Knowledge and experience in statistical and data mining techniques: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
    • A specialization in text analytics, image recognition, graph analysis or other specialized ML techniques such as deep learning, etc., is preferred.
    • Ideally, the candidates are adept in agile methodologies and well-versed in applying DevOps/MLOps methods to the construction of ML and data science pipelines.
    • Knowledge of industry standard BA tools, including Cognos, QlikView, Business Objects, and other tools that could be used for enterprise solutions
    • Should exhibit superior presentation skills, including storytelling and other techniques to guide and inspire and explain analytics capabilities and techniques to the organization.
Coolblue
  • Rotterdam, Netherlands
As an Advanced Data Analyst / Data Scientist you use the data of millions of visitors to help Coolblue act smarter.

Pros and cons

  • Youre going to be working as a true Data Scientist. One who understands why you get the results that you do and apply this information to other experiments.
  • Youre able to use the right tools for every job.
  • Your job starts with a problem and ends with you monitoring your own solution.
  • You have to crawl underneath the foosball table when you lose a game.

Description Data Scientist

Your challenge in this sprint is improving the weekly sales forecasting models for the Christmas period. Your cross-validation strategy is ready, but before you can begin, you have to query the data from our systems and process them in a way that allows you to view the situation with clarity.

First, you have a meeting with Matthias, whos worked on this problem before. During your meeting, you conclude that Christmas has a non-linear effect on sales.  Thats why you decide to experiment with a multiplicative XGBoost in addition to your Regularised-Regression model. You make a grid with various features and parameters for both models and analyze the effects of both approaches. You notice your Regression is overfitting, which means XGBoost isnt performing and the forecast isnt high enough, so you increase the regularization and appoint the Christmas features to XGBoost alone.

Nice! You improved the precision of the Christmas forecast with an average of 2%. This will only yield results once the algorithm has been implemented, so you start thinking about how you want to implement this.

Your specifications

  • You have at least 4 years of experience in a similar function.
  • You have a university degree, MSC, or PHD in Mathematics, Computer Science, or Statistics.
  • You have experience with Machine Learning techniques, such as Gradient Boosting, Random Forest, and Neutral Networks, and you have proven experience with successfully applying these (or similar) techniques in a business environment.
  • You have some experience with Data mining, SQL, BigQuery, NoSQL, R, and monitoring.
  • You're highly knowledgeable about Python.
  • You have experience with Big Data technologies, such as Spark and Hadoop.

Included by default.

  • Money.
  • Travel allowance and a retirement plan.
  • 25 leave days. As long as you promise to come back.
  • A discount on all our products.
  • A picture-perfect office at a great location. You could crawl to work from Rotterdam Central Station. Though we recommend just walking for 2 minutes.
  • A horizontal organisation in the broadest sense. You could just go and have a beer with the boss.

Review



'I believe I'm working in a great team of enthusiastic and smart people, with a good mix of juniors and seniors. The projects that we work on are very interesting and diverse, think of marketing, pricing and recommender systems. For each project we try to use the latest research and machine learning techniques in order to create the best solutions. I like that we are involved in the projects start to end, from researching the problem to experimenting, to putting it in production, and to creating the monitoring dashboards and delivering the outputs on a daily basis to our stakeholders. The work environment is open, relaxed and especially fun'
- Cheryl Zandvliet, Data Scientist
State Farm
  • Atlanta, GA

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

For over 95 years, data has been key to State Farm.  As a member of our data science team with the Enterprise Data & Analytics department under our Chief Data & Analytics Officer, you will work across the organization to solve business problems and help achieve business strategies.  You will employ sophisticated, statistical approaches and state of the art technology.  You will build and refine our tools/techniques and engage w/internal stakeholders across the organization to improve our products & services.


Implementing solutions is critical for success. You will do problem identification, solution proposal & presentation to a wide variety of management & technical audiences. This challenging career requires you to work on multiple concurrent projects in a community setting, developing yourself and others, and advancing data science both at State Farm and externally.


Skills & Professional Experience

·        Develop hypotheses, design experiments, and test feasibility of proposed actions to determine probable outcomes using a variety of tools & technologies

·        Masters, other advanced degrees, or five years experience in an analytical field such as data science quantitative marketing, statistics, operations research, management science, industrial engineering, economics, etc. or equivalent practical experience preferred.

·        Experience with SQL, Python, R, Java, SAS or MapReduce, SPARK

·        Experience with unstructured data sets: text analytics, image recognition etc.

·        Experience working w/numerous large data sets/data warehouses & ability to pull from such data sets using relevant programs & coding including files, RDBMS & Hadoop based storage systems

·        Knowledge in machine learning methods including at least one of the following: Time series analysis, Hierarchical Bayes; or learning techniques such as Decision Trees, Boosting, Random Forests.

·        Excellent communication skills and the ability to manage multiple diverse stakeholders across businesses & leadership levels.

·        Exercise sound judgment to diagnose & resolve problems within area of expertise

·        Familiarity with CI/CD development methods, Git and Docker a plus


Multiple location opportunity. Locations offered are: Atlanta, GA, Bloomington, IL, Dallas, TX and Phoenix, AZ


Remote work option is not available.


There is no sponsorship for an employment visa for the position at this time.


Competencies desired:
Critical Thinking
Leadership
Initiative
Resourcefulness
Relationship Building
State Farm
  • Dallas, TX

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

For over 95 years, data has been key to State Farm.  As a member of our data science team with the Enterprise Data & Analytics department under our Chief Data & Analytics Officer, you will work across the organization to solve business problems and help achieve business strategies.  You will employ sophisticated, statistical approaches and state of the art technology.  You will build and refine our tools/techniques and engage w/internal stakeholders across the organization to improve our products & services.


Implementing solutions is critical for success. You will do problem identification, solution proposal & presentation to a wide variety of management & technical audiences. This challenging career requires you to work on multiple concurrent projects in a community setting, developing yourself and others, and advancing data science both at State Farm and externally.


Skills & Professional Experience

·        Develop hypotheses, design experiments, and test feasibility of proposed actions to determine probable outcomes using a variety of tools & technologies

·        Masters, other advanced degrees, or five years experience in an analytical field such as data science quantitative marketing, statistics, operations research, management science, industrial engineering, economics, etc. or equivalent practical experience preferred.

·        Experience with SQL, Python, R, Java, SAS or MapReduce, SPARK

·        Experience with unstructured data sets: text analytics, image recognition etc.

·        Experience working w/numerous large data sets/data warehouses & ability to pull from such data sets using relevant programs & coding including files, RDBMS & Hadoop based storage systems

·        Knowledge in machine learning methods including at least one of the following: Time series analysis, Hierarchical Bayes; or learning techniques such as Decision Trees, Boosting, Random Forests.

·        Excellent communication skills and the ability to manage multiple diverse stakeholders across businesses & leadership levels.

·        Exercise sound judgment to diagnose & resolve problems within area of expertise

·        Familiarity with CI/CD development methods, Git and Docker a plus


Multiple location opportunity. Locations offered are: Atlanta, GA, Bloomington, IL, Dallas, TX and Phoenix, AZ


Remote work option is not available.


There is no sponsorship for an employment visa for the position at this time.


Competencies desired:
Critical Thinking
Leadership
Initiative
Resourcefulness
Relationship Building
Coolblue
  • Rotterdam, Netherlands
As an Advanced Data Analyst / Data Scientist you use the data of millions of visitors to help Coolblue act smarter.

Pros and cons

  • Youre going to be working as a true Data Scientist. One who understands why you get the results that you do and apply this information to other experiments.
  • Youre able to use the right tools for every job.
  • Your job starts with a problem and ends with you monitoring your own solution.
  • You have to crawl underneath the foosball table when you lose a game.

Description Data Scientist

Your challenge in this sprint is improving the weekly sales forecasting models for the Christmas period. Your cross-validation strategy is ready, but before you can begin, you have to query the data from our systems and process them in a way that allows you to view the situation with clarity.

First, you have a meeting with Matthias, whos worked on this problem before. During your meeting, you conclude that Christmas has a non-linear effect on sales.  Thats why you decide to experiment with a multiplicative XGBoost in addition to your Regularised-Regression model. You make a grid with various features and parameters for both models and analyze the effects of both approaches. You notice your Regression is overfitting, which means XGBoost isnt performing and the forecast isnt high enough, so you increase the regularization and appoint the Christmas features to XGBoost alone.

Nice! You improved the precision of the Christmas forecast with an average of 2%. This will only yield results once the algorithm has been implemented, so you start thinking about how you want to implement this.

Your specifications

  • You have at least 4 years of experience in a similar function.
  • You have a university degree, MSC, or PHD in Mathematics, Computer Science, or Statistics.
  • You have experience with Machine Learning techniques, such as Gradient Boosting, Random Forest, and Neutral Networks, and you have proven experience with successfully applying these (or similar) techniques in a business environment.
  • You have some experience with Data mining, SQL, BigQuery, NoSQL, R, and monitoring.
  • You're highly knowledgeable about Python.
  • You have experience with Big Data technologies, such as Spark and Hadoop.

Included by default.

  • Money.
  • Travel allowance and a retirement plan.
  • 25 leave days. As long as you promise to come back.
  • A discount on all our products.
  • A picture-perfect office at a great location. You could crawl to work from Rotterdam Central Station. Though we recommend just walking for 2 minutes.
  • A horizontal organisation in the broadest sense. You could just go and have a beer with the boss.

Review



'I believe I'm working in a great team of enthusiastic and smart people, with a good mix of juniors and seniors. The projects that we work on are very interesting and diverse, think of marketing, pricing and recommender systems. For each project we try to use the latest research and machine learning techniques in order to create the best solutions. I like that we are involved in the projects start to end, from researching the problem to experimenting, to putting it in production, and to creating the monitoring dashboards and delivering the outputs on a daily basis to our stakeholders. The work environment is open, relaxed and especially fun'
- Cheryl Zandvliet, Data Scientist
MSH Talent Solutions
  • Phoenix, AZ

Our client is embarking on an exciting transformation driven by a high-energy newly formed Machine Learning team of high performers that is looking to build the next generation platform for democratizing Machine Learning in Amex on the Cloud. This group is nimble and creative with the power to craft our technology and product roadmap.


As an Engineer in our Machine Learning team, you will be responsible for building and delivering technical solutions and capabilities on the platform to support our entire ML-driven application portfolio across the enterprise. You will be challenged with identifying creative ideas and proof of concepts to deliver against the existing and future needs of our customers. 


As an Engineer, you will play a key role in the understanding of product owner strategy and collaborate with peers and technology partners to translate complex user stories into successful product releases. If you have the talent and desire to deliver innovative products and services at a rapid pace, serving our customers seamlessly across through cognitive solutions, this would be the right fit for you!


Your responsibilities would include:

    • More than 80%+ of the time spent on coding and/or hands-on technical implementation of re-usable frameworks to drive adoption of Machine Learning in the Enterprise
    • Collaborate with product/business management and engineering departments to understand company needs and devise possible solutions.
    • Leading your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.
    • Architecting, estimating and planning technical solutions to problems
    • Research and develop statistical learning models for data analysis
    • Implement new, highly scalable platform components and tools using machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing, Results Prediction and Time Series predictions
    • Actively participate in team and company-wide architecture and engineering discussions and forums


Qualifications:

To be successful in the role, the following experience is required:

    • At least 3+ years of dynamic experience with a broad set of tech stacks, hands-on Machine Learning and Big Data is mandatory as part of the job
    • At least 3+ years of Python experience.
    • Deep expertise in building scalable Machine Learning powered applications
    • Experience with production grade applications. Ideally with an application that demonstrates Machine Learning to power its decisions
    • Highly motivated, individual contributor who can manage relationships in a cross-functional environment.
    • Proven track record of working with multiple stakeholders
    • Extensive background in data mining and statistical analysis
    • Excellent pattern recognition and predictive modeling skills
    • Prefer Experience in creating and managing capabilities and solutions for :
      • Customer segmentation
      • Product sales and service offer prediction
      • Risk analytics and regulation
      • Usage and Alert from real time data
      • Customer complaint resolution
      • Consumer feedback and interaction analysis
    • Familiarity and experience with Cloud is a plus.


Quantitative and Software Development Skills

    • Master of Science or higher in a quantitative discipline, e.g. Data Science, Statistics , Mathematics, Computer Sciences or similar Bachelor of Science with 5 years of experience in a highly quantitative position
    • High proficiency with the following technologies:
        • Spark, SparkML
        • Python
        • Big Data
        • SQL / noSQL
        • Java
        • Web Frameworks : Flask, Django
        • Git and GitHub
    • Modeling proficiency:
        • Linear models & descriptive statistics
        • Natural Language Processing
        • Bayesian Inference
        • Decision Tree Models & Boosting
        • Advanced time series forecasting
        • Linear Algebra & Spectral Methods
        • Deep Learning / Tensorflow / Keras
        • Reinforcement Learning
    • Have the ability to design or evaluate intrinsic and extrinsic metrics of your models performance which are aligned with business goals.
    • Performing hands-on software and strategy development, typically spending most of the time actually writing code, doing proof of concepts and conducting code reviews
    • Developing deep understanding of integrations with other systems and platforms within the supported domains.
    • Working with technical product managers contributing to blueprints, and assisting needs and predicting of feature sets
    • Quickly generate and updating prototypes from concept to testing while soliciting feedback
    • Finalizing prototypes into functional ML components and deploy on our cloud platform
    • Embrace emerging standards and promoting best practices
Coolblue
  • Rotterdam, Netherlands
As an Advanced Data Analyst / Data Scientist you use the data of millions of visitors to help Coolblue act smarter.

Pros and cons

  • Youre going to be working as a true Data Scientist. One who understands why you get the results that you do and apply this information to other experiments.
  • Youre able to use the right tools for every job.
  • Your job starts with a problem and ends with you monitoring your own solution.
  • You have to crawl underneath the foosball table when you lose a game.

Description Data Scientist

Your challenge in this sprint is improving the weekly sales forecasting models for the Christmas period. Your cross-validation strategy is ready, but before you can begin, you have to query the data from our systems and process them in a way that allows you to view the situation with clarity.

First, you have a meeting with Matthias, whos worked on this problem before. During your meeting, you conclude that Christmas has a non-linear effect on sales.  Thats why you decide to experiment with a multiplicative XGBoost in addition to your Regularised-Regression model. You make a grid with various features and parameters for both models and analyze the effects of both approaches. You notice your Regression is overfitting, which means XGBoost isnt performing and the forecast isnt high enough, so you increase the regularization and appoint the Christmas features to XGBoost alone.

Nice! You improved the precision of the Christmas forecast with an average of 2%. This will only yield results once the algorithm has been implemented, so you start thinking about how you want to implement this.

Your specifications

  • You have at least 6 years of experience in a similar function.
  • You have a university degree, MSC, or PHD in Mathematics, Computer Science, or Statistics.
  • You have experience with Machine Learning techniques, such as Gradient Boosting, Random Forest, and Neutral Networks, and you have proven experience with successfully applying these (or similar) techniques in a business environment.
  • You have some experience with Data mining, SQL, BigQuery, NoSQL, R, and monitoring.
  • You're highly knowledgeable about Python.
  • You have experience with Big Data technologies, such as Spark and Hadoop.

Included by default.

  • Money.
  • Travel allowance and a retirement plan.
  • 25 leave days. As long as you promise to come back.
  • A discount on all our products.
  • A picture-perfect office at a great location. You could crawl to work from Rotterdam Central Station. Though we recommend just walking for 2 minutes.
  • A horizontal organisation in the broadest sense. You could just go and have a beer with the boss.
Wallethub
  • No office location
  • Salary: $36k - 72k

Company details


WalletHub is one of the leading personal finance destinations in the US and rapidly growing. We're looking for a highly experienced and motivated Data Scientist for a full-time, permanent position.


The main objective of the Data Science Team is to improve WalletHub's services and core product. This has a direct impact on the overall user experience.


Making the right personal finance decisions by sifting through vast amounts of available information can be a daunting task for almost anyone. This is because a large number of interrelated factors need to be taken into account when making such decisions.


By designing and constructing data-driven models, the Data Science Team is able to provide our users with indispensable knowledge and meaningful advice on how they can achieve their personal finance goals.


Such goals include:



  • Selecting the best financial products for your needs

  • Taking the right actions to improve your credit score

  • Anticipate your future financial health based on your current financial status and history


With these goals in mind, our Data Scientists use the latest cloud technologies and machine learning tools in order to exploit the potential of data analytics. We always have new and interesting projects on the horizon that aim to help our users reach their personal finance aspirations!


Requirements


You are the ideal candidate for this job if you have:



  • At least 5 years experience in Java, Spring and MySQL (or any relational database) and Python.

  • At least 2 years of experience as a Data Scientist.

  • Experience with databases (including NoSQL).

  • Experience in machine learning frameworks and libraries.

  • Supervised and Unsupervised learning.

  • Machine learning concepts and techniques: Regularization, Boosting, Random Forests, Decision Trees, Bayesian models, Neural networks, Support Vector Machines (SVM).

  • Experience with the whole ETL data cycle (extract, validate, transform, clean, aggregate, audit, archive).

  • Computer Science or Mathematics or Physics degree.

  • Excellent communication and analytical skills.

  • Willingness to work hard (50 hrs per week).

  • Very good English


Nice to have but not required



  • Experience with Apache Spark.

  • Natural Language Processing (tokenization, tagging, sentiment analysis, entity recognition, summarization).

  • R programming language.


Responsibilities



  • Modeling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques.

  • Participating in the areas of architecture, design, implementation, and testing.

  • Proposing innovative ways to look at problems by using data mining approaches on the set of information available.

  • Designing experiments, testing hypotheses, and building models.

  • Conducting advanced data analysis and designing highly complex algorithm.

  • Applying advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems.


Our Offer



  • Very competitive salary based on prior experience and qualifications.

  • Potential for stock options after the first year.

  • Raise and advancement opportunities based on periodic evaluations.

  • Visa sponsorship (if working from outside the US, sponsorship can be granted after 18 months with the company, based on performance).

  • Health benefits (in case you will be working from our office in Washington DC).


Notes 



  • This position does not have a location requirement and can be performed either remotely (including from outside the U.S.) or from WalletHub’s offices in downtown Washington DC.

  • If you're intending to work from outside the US please be aware this position entails working at least 50 hour per week and requires an overlap with EST business hours.


More about WalletHub


WalletHub is a high-growth fintech company based in Washington, DC that is looking for talented, hard-working individuals to help us reshape personal finance. More specifically, we are harnessing the power of data analytics and artificial intelligence to build the brain of a smart financial advisor, whose services we’re offering to everyone for free. The WalletHub brain enables users to make better financial decisions in a fraction of the time with three unique features:


1) Customized Credit-Improvement Tips: WalletHub identifies improvement opportunities and guides you through the necessary corrections.


2) Personalized Money-Saving Advice: WalletHub’s savings brain constantly scours the market for load-lightening opportunities, bringing you only the best deals.


3) Wallet Surveillance: Personal finance isn’t as scary with 24/7 credit monitoring providing backup, notifying you of important credit-report changes.


In addition to the valuable intelligence the brain provides, WalletHub is the first and only service to offer free credit scores and full credit reports that are updated on a daily basis absent of user interaction, rather than weekly or monthly and only when a user logs in. Some other services hang their hats on free credit scores and reports, yet they’re still inferior to what WalletHub considers minor pieces to a much larger puzzle.


How to Apply

To get our attention, all you need to do is send us a resume. If we believe that you will be a good match, we'll contact you to arrange the next steps. You can apply directly on Stackoverflow or email your application to jobs.dev@wallethub.com

Wallethub
  • Washington, DC

Company details


WalletHub is one of the leading personal finance destinations in the US and rapidly growing. We're looking for a highly experienced and motivated Data Scientist for a full-time, permanent position.


The main objective of the Data Science Team is to improve WalletHub's services and core product. This has a direct impact on the overall user experience.


Making the right personal finance decisions by sifting through vast amounts of available information can be a daunting task for almost anyone. This is because a large number of interrelated factors need to be taken into account when making such decisions.


By designing and constructing data-driven models, the Data Science Team is able to provide our users with indispensable knowledge and meaningful advice on how they can achieve their personal finance goals.


Such goals include:



  • Selecting the best financial products for your needs

  • Taking the right actions to improve your credit score

  • Anticipate your future financial health based on your current financial status and history


With these goals in mind, our Data Scientists use the latest cloud technologies and machine learning tools in order to exploit the potential of data analytics. We always have new and interesting projects on the horizon that aim to help our users reach their personal finance aspirations!


Requirements


You are the ideal candidate for this job if you have:



  • At least 5 years experience in Java, Spring and MySQL (or any relational database) and Python.

  • Experience with databases (including NoSQL).

  • Experience in machine learning frameworks and libraries.

  • Supervised and Unsupervised learning.

  • Machine learning concepts and techniques: Regularization, Boosting, Random Forests, Decision Trees, Bayesian models, Neural networks, Support Vector Machines (SVM).

  • Experience with the whole ETL data cycle (extract, validate, transform, clean, aggregate, audit, archive).

  • Computer Science or Mathematics or Physics degree.

  • Excellent communication and analytical skills.

  • Willingness to work hard (50 hrs per week).

  • Very good English


Nice to have but not required



  • Experience with Apache Spark.

  • Natural Language Processing (tokenization, tagging, sentiment analysis, entity recognition, summarization).

  • R programming language.


Responsibilities



  • Modeling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques.

  • Participating in the areas of architecture, design, implementation, and testing.

  • Proposing innovative ways to look at problems by using data mining approaches on the set of information available.

  • Designing experiments, testing hypotheses, and building models.

  • Conducting advanced data analysis and designing highly complex algorithm.

  • Applying advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems.


Our Offer



  • Very competitive salary based on prior experience and qualifications.

  • Potential for stock options after the first year.

  • Raise and advancement opportunities based on periodic evaluations.

  • Visa sponsorship (if working from outside the US, sponsorship can be granted after 18 months with the company, based on performance).

  • Health benefits (in case you will be working from our office in Washington DC).


Notes 



  • This position does not have a location requirement and can be performed either remotely (including from outside the U.S.) or from WalletHub’s offices in downtown Washington DC.

  • If you're intending to work from outside the US please be aware this position entails working at least 50 hour per week and requires an overlap with EST business hours.


More about WalletHub


WalletHub is a high-growth fintech company based in Washington, DC that is looking for talented, hard-working individuals to help us reshape personal finance. More specifically, we are harnessing the power of data analytics and artificial intelligence to build the brain of a smart financial advisor, whose services we’re offering to everyone for free. The WalletHub brain enables users to make better financial decisions in a fraction of the time with three unique features:


1) Customized Credit-Improvement Tips: WalletHub identifies improvement opportunities and guides you through the necessary corrections.


2) Personalized Money-Saving Advice: WalletHub’s savings brain constantly scours the market for load-lightening opportunities, bringing you only the best deals.


3) Wallet Surveillance: Personal finance isn’t as scary with 24/7 credit monitoring providing backup, notifying you of important credit-report changes.


In addition to the valuable intelligence the brain provides, WalletHub is the first and only service to offer free credit scores and full credit reports that are updated on a daily basis absent of user interaction, rather than weekly or monthly and only when a user logs in. Some other services hang their hats on free credit scores and reports, yet they’re still inferior to what WalletHub considers minor pieces to a much larger puzzle.


How to Apply

To get our attention, all you need to do is send us a resume. If we believe that you will be a good match, we'll contact you to arrange the next steps. You can apply directly on Stackoverflow or email your application to jobs.dev@wallethub.com

Wallethub
  • Washington, DC

Company details


WalletHub is one of the leading personal finance destinations in the US and rapidly growing. We're looking for a highly experienced and motivated Data Scientist for a full-time, permanent position.


The main objective of the Data Science Team is to improve WalletHub's services and core product. This has a direct impact on the overall user experience.


Making the right personal finance decisions by sifting through vast amounts of available information can be a daunting task for almost anyone. This is because a large number of interrelated factors need to be taken into account when making such decisions.


By designing and constructing data-driven models, the Data Science Team is able to provide our users with indispensable knowledge and meaningful advice on how they can achieve their personal finance goals.


Such goals include:



  • Selecting the best financial products for your needs

  • Taking the right actions to improve your credit score

  • Anticipate your future financial health based on your current financial status and history


With these goals in mind, our Data Scientists use the latest cloud technologies and machine learning tools in order to exploit the potential of data analytics. We always have new and interesting projects on the horizon that aim to help our users reach their personal finance aspirations!


Requirements


You are the ideal candidate for this job if you have:



  • At least 5 years experience in Java, Spring and MySQL (or any relational database) and Python

  • Experience with databases (including NoSQL)

  • Experience in machine learning frameworks and libraries

  • Supervised and Unsupervised learning

  • Machine learning concepts and techniques: Regularization, Boosting, Random Forests, Decision Trees, Bayesian models, Neural networks, Support Vector Machines (SVM)

  • Experience with the whole ETL data cycle (extract, validate, transform, clean, aggregate, audit, archive)

  • Computer Science or Mathematics or Physics degree

  • Excellent communication and analytical skills

  • Willingness to work hard (50 hrs per week)

  • Very good English


Nice to have but not required



  • Experience with Apache Spark

  • Natural Language Processing (tokenization, tagging, sentiment analysis, entity recognition, summarization)

  • R programming language


Responsibilities



  • Modeling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques

  • Participating in the areas of architecture, design, implementation, and testing

  • Proposing innovative ways to look at problems by using data mining approaches on the set of information available

  • Designing experiments, testing hypotheses, and building models

  • Conducting advanced data analysis and designing highly complex algorithm

  • Applying advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems


Our Offer



  • Very competitive salary based on prior experience and qualifications

  • Potential for stock options after the first year

  • Raise and advancement opportunities based on periodic evaluations

  • Visa sponsorship (if working from outside the US, sponsorship can be granted after 18 months with the company, based on performance).

  • Health benefits (in case you will be working from our office in Washington DC)


Notes 



  • This position does not have a location requirement and can be performed either remotely (including from outside the U.S.) or from WalletHub’s offices in downtown Washington DC.

  • If you're intending to work from outside the US please be aware this position entails working at least 50 hour per week and requires an overlap with EST business hours.


More about WalletHub


WalletHub is a high-growth fintech company based in Washington, DC that is looking for talented, hard-working individuals to help us reshape personal finance. More specifically, we are harnessing the power of data analytics and artificial intelligence to build the brain of a smart financial advisor, whose services we’re offering to everyone for free. The WalletHub brain enables users to make better financial decisions in a fraction of the time with three unique features:


1) Customized Credit-Improvement Tips: WalletHub identifies improvement opportunities and guides you through the necessary corrections.


2) Personalized Money-Saving Advice: WalletHub’s savings brain constantly scours the market for load-lightening opportunities, bringing you only the best deals.


3) Wallet Surveillance: Personal finance isn’t as scary with 24/7 credit monitoring providing backup, notifying you of important credit-report changes.


In addition to the valuable intelligence the brain provides, WalletHub is the first and only service to offer free credit scores and full credit reports that are updated on a daily basis absent of user interaction, rather than weekly or monthly and only when a user logs in. Some other services hang their hats on free credit scores and reports, yet they’re still inferior to what WalletHub considers minor pieces to a much larger puzzle.


How to Apply

To get our attention, all you need to do is send us a resume. If we believe that you will be a good match, we'll contact you to arrange the next steps. You can apply directly on Stackoverflow or email your application to jobs.dev@wallethub.com

Capgemini
  • Atlanta, GA

 Data Science Senior Manager:

The Data Science & Analytics practice group at Capgemini is expanding its footprintrapidly. As part of the fastest growing digital practice within Capgemini, we work with the latest advanced analytics, machine learning, and big data technologies to extract meaning and value from data in a number of different industries ranging from Media & Entertainment to Life Sciences and everywhere in-between. Our team has worked with geospatial data, on social media sentiment analysis, built recommendation systems, created image classification algorithms, solved large-scale optimization problems, and harnessed the massive influx of data generated by the IoT.


The Data Science & Analytics group is the fastest growing digital practice at Capgemini demanding agile innovation. As part of the Data Science & Analytics group, you will work in a collaborative environment with internal and client resources to understand key business goals, build solutions, and present findings to client executives while solving real-world problems. If you are passionate about solving problems in the realm of cognitive computing, big data, and machine learning while utilizing business acumen, statistical understanding, and technical know-how, the Data Science & Analytics practice group at Capgemini is the best place to grow your career.


Role & Responsibilities:
     Develop
    • analytics practice including consulting management, practice and business development with a strong of broad-based experience in diverse industries
  • Generate and execute the Data Science roadmap strategy for practice
  • Develop internal industry solutions with management for practice
  • Provide guidance on overall practice to ensure successful delivery while balancing internal initiatives
  • Quickly understand client needs, assemble teams, manage delivery, and articulate findings to client executives
  • Prospect, generate, and deliver new business opportunities in given sector to meet revenue targets
  • Analyze and model both structured and unstructured data from a number of distributed client and publicly available sources
  • Perform EDA and feature engineering to both inform the development of statistical models and generate improve model performance and flexibility.
  • Mentor and develop team
  • Grow data science practice by meeting business goals through client prospecting, responding to proposals, identifying and closing opportunities within identified client accounts
  • Participate in client discussions, interact with CxOs at client organization to articulate the value of data science approaches, different service offerings and guide them on implementation of the same
  • Collaborate with client managers in a broad range of sectors to identify business use cases and develop solutions in driving impact through data science and analytics, communicate results, and inform practice group through reports and presentations
  • Develop, enhance, and maintain client relations while ensuring client satisfaction
  • Ability to successfully deliver and manage multiple client engagements globally


Requirements:

  • 10+ years professional work experience as a data scientist or on advanced analytics / statistics projects  
  • MUST POSSESS CONSULTING EXPERIENCE
  • Masters degree or PhD in Computer Science, Statistics, Economics, Physics, Engineering, Mathematics, or other closely related field.  
  • Strong understanding and application of statistical methods and skills: distributions, experimental design, variance analysis, A/B testing, and regression.
  • Possess executive presence and ability to drive senior executive thinking
  • Value engineering (distilling a business case)
  • Consulting engagement management / economics
  • Skilled with practice / business development
  • Statistical emphasis on data mining techniques, Bayesian Networks Inference, CHAID, CART, association rule, linear and non-linear regression, hierarchical mixed models/multi-level modeling, and ability to answer questions about underlying algorithms and processes.
  • Experience with both Bayesian and frequentist methodologies.
  • Mastery of statistical software, scripting languages, and packages (e.g. R, Matlab, SAS, Python, Pearl, Scikit-learn, Caffe, SAP Predictive Analytics, KXEN, ect.).
  • Knowledge of or experience working with database systems (e.g. SQL, NoSQL, MongoDB, Postgres, ect.)
  • Experience working with big data distributed programming languages, and ecosystems (e.g. S3, EC2, Hadoop/MapReduce, Pig, Hive, Spark, SAP HANA, ect.)
  • Expertise in machine learning algorithms and experience using the following ML techniques: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Time Series, KMeans, Clustering, NMF).
  • Preferred experience with NLP, Graph Theory, Neural Networks (RNNs/CNNs), sentiment analysis, and Azure ML..
  • Experience building scalable data pipelines and with data engineering/ feature engineering.
  • Preferred experience with web-scrapping.
  • Experience building and deploying predictive models.
  • Expertise using PowerPoint and clearly articulating findings/ presenting solutions.
  • Excellent team-oriented interpersonal skills and demonstrated leadership.
  • Track record delivering successful data science projects and managing global teams.
  • Demonstrated leadership by building Data Science teams and fostering growth.
  • Proven success generating growth and hitting revenue targets.
State Farm
  • Atlanta, GA

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

For over 95 years, data has been key to State Farm.  As a member of our data science team with the Enterprise Data & Analytics department under our Chief Data & Analytics Officer, you will work across the organization to solve business problems and help achieve business strategies.  You will employ sophisticated, statistical approaches and state of the art technology.  You will build and refine our tools/techniques and engage w/internal stakeholders across the organization to improve our products & services.


Implementing solutions is critical for success. You will do problem identification, solution proposal & presentation to a wide variety of management & technical audiences. This challenging career requires you to work on multiple concurrent projects in a community setting, developing yourself and others, and advancing data science both at State Farm and externally.


Skills & Professional Experience

·        Develop hypotheses, design experiments, and test feasibility of proposed actions to determine probable outcomes using a variety of tools & technologies

·        Masters, other advanced degrees, or five years experience in an analytical field such as data science quantitative marketing, statistics, operations research, management science, industrial engineering, economics, etc. or equivalent practical experience preferred.

·        Experience with SQL, Python, R, Java, SAS or MapReduce, SPARK

·        Experience with unstructured data sets: text analytics, image recognition etc.

·        Experience working w/numerous large data sets/data warehouses & ability to pull from such data sets using relevant programs & coding including files, RDBMS & Hadoop based storage systems

·        Knowledge in machine learning methods including at least one of the following: Time series analysis, Hierarchical Bayes; or learning techniques such as Decision Trees, Boosting, Random Forests.

·        Excellent communication skills and the ability to manage multiple diverse stakeholders across businesses & leadership levels.

·        Exercise sound judgment to diagnose & resolve problems within area of expertise

·        Familiarity with CI/CD development methods, Git and Docker a plus

Multiple location opportunity. Locations offered are: Atlanta, GA, Bloomington, IL, Dallas, TX and Phoenix, AZ

Remote work option is not available.


There is no sponsorship for an employment visa for the position at this time.


Competencies desired:
Critical Thinking
Leadership
Initiative
Resourcefulness
Relationship Building





State Farm
  • Atlanta, GA

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

For over 95 years, data has been key to State Farm.  As a member of our data science team with the Enterprise Data & Analytics department under our Chief Data & Analytics Officer, you will work across the organization to solve business problems and help achieve business strategies.  You will employ sophisticated, statistical approaches and state of the art technology.  You will build and refine our tools/techniques and engage w/internal stakeholders across the organization to improve our products & services.


Implementing solutions is critical for success. You will do problem identification, solution proposal & presentation to a wide variety of management & technical audiences. This challenging career requires you to work on multiple concurrent projects in a community setting, developing yourself and others, and advancing data science both at State Farm and externally.


Skills & Professional Experience

·        Develop hypotheses, design experiments, and test feasibility of proposed actions to determine probable outcomes using a variety of tools & technologies

·        Masters, other advanced degrees, or five years experience in an analytical field such as data science quantitative marketing, statistics, operations research, management science, industrial engineering, economics, etc. or equivalent practical experience preferred.

·        Experience with SQL, Python, R, Java, SAS or MapReduce, SPARK

·        Experience with unstructured data sets: text analytics, image recognition etc.

·        Experience working w/numerous large data sets/data warehouses & ability to pull from such data sets using relevant programs & coding including files, RDBMS & Hadoop based storage systems

·        Knowledge in machine learning methods including at least one of the following: Time series analysis, Hierarchical Bayes; or learning techniques such as Decision Trees, Boosting, Random Forests.

·        Excellent communication skills and the ability to manage multiple diverse stakeholders across businesses & leadership levels.

·        Exercise sound judgment to diagnose & resolve problems within area of expertise

·        Familiarity with CI/CD development methods, Git and Docker a plus


Multiple location opportunity. Locations offered are: Atlanta, GA, Bloomington, IL, Dallas, TX and Phoenix, AZ


Remote work option is not available.


There is no sponsorship for an employment visa for the position at this time.


Competencies desired:
Critical Thinking
Leadership
Initiative
Resourcefulness
Relationship Building
State Farm
  • Dallas, TX

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

WHAT ARE THE DUTIES AND RESPONSIBILITIES OF THIS POSITION?

    Perfo
    • rms improved visual representation of data to allow clearer communication, viewer engagement and faster/better decision-making Inves
    • tigates, recommends, and initiates acquisition of new data resources from internal and external sources Works
    • with IT teams to support data collection, integration, and retention requirements based on business need Ident
    • ifies critical and emerging technologies that will support and extend quantitative analytic capabilities Manag
    • es work efforts which require the use of sophisticated project planning techniques Appli
    • es a wide application of complex principles, theories and concepts in a specific field to provide solutions to a wide range of difficult problems Devel
    • ops and maintains an effective network of both scientific and business contacts/knowledge obtaining relevant information and intelligence around the market and emergent opportunities Contr
    • ibutes data to State Farm's internal and external publications, write articles for leading journals and participate in academic and industry conferences
    • Collaborates with business subject matter experts to select relevant sources of information
    • Develop breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop)
    • Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling, graph theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation
    • Develop expertise with State Farm datasets, data repositories, and data movement processes
    • Assists on projects/requests and may lead specific tasks within the project scope
    • Prepares and manipulates data for use in development of statistical models
    • Develops fundamental understanding of insurance and financial services operations and uses this knowledge in decision making


Additional Details:

For over 95 years, data has been key to State Farm.  As a member of our data science team with the Enterprise Data & Analytics department under our Chief Data & Analytics Officer, you will work across the organization to solve business problems and help achieve business strategies.  You will employ sophisticated, statistical approaches and state of the art technology.  You will build and refine our tools/techniques and engage w/internal stakeholders across the organization to improve our products & services.


Implementing solutions is critical for success. You will do problem identification, solution proposal & presentation to a wide variety of management & technical audiences. This challenging career requires you to work on multiple concurrent projects in a community setting, developing yourself and others, and advancing data science both at State Farm and externally.


Skills & Professional Experience

·        Develop hypotheses, design experiments, and test feasibility of proposed actions to determine probable outcomes using a variety of tools & technologies

·        Masters, other advanced degrees, or five years experience in an analytical field such as data science quantitative marketing, statistics, operations research, management science, industrial engineering, economics, etc. or equivalent practical experience preferred.

·        Experience with SQL, Python, R, Java, SAS or MapReduce, SPARK

·        Experience with unstructured data sets: text analytics, image recognition etc.

·        Experience working w/numerous large data sets/data warehouses & ability to pull from such data sets using relevant programs & coding including files, RDBMS & Hadoop based storage systems

·        Knowledge in machine learning methods including at least one of the following: Time series analysis, Hierarchical Bayes; or learning techniques such as Decision Trees, Boosting, Random Forests.

·        Excellent communication skills and the ability to manage multiple diverse stakeholders across businesses & leadership levels.

·        Exercise sound judgment to diagnose & resolve problems within area of expertise

·        Familiarity with CI/CD development methods, Git and Docker a plus


Multiple location opportunity. Locations offered are: Atlanta, GA, Bloomington, IL, Dallas, TX and Phoenix, AZ


Remote work option is not available.


There is no sponsorship for an employment visa for the position at this time.


Competencies desired:
Critical Thinking
Leadership
Initiative
Resourcefulness
Relationship Building
LLamasoft, Inc.
  • Detroit, MI

Like Stats?  
Yeah, us too!

Check these:


600+ enterprise customers in 60 countries

50% of Fortune 100 companies are customers

24 of the Gartner Top 25 Supply Chain are customers


So, yes, were all about business.  But were also all about sustainability, see our 2017 Green Award **
 

ICYMI: We were named to the 2017 Best and Brightest Company in the US of A and in Metro Detroits 2017 Best and Brightest Company list

Were well funded, fun and focused on building the very best in supply chain and we want YOU to help us build complex models that allow global companies to quickly, safely model supply chain impacts.

Dont believe us - read the Gartner Supply Chain Masters and youll learn that nearly all of the Gartner Supply Chain Top 25 use our solutions to tackle the most complex supply chains issues the world has ever seen.

Smart, energetic and ready to make your mark in a best in class enterprise software company?  Join our herd!


** from Supply and Demand Chain Executive


Job Description:  

  • Research, design and prototype novel models based on machine learning, data mining, and statistical modeling to solve hard analytics problems, where the problems may range from exploratory to highly applied
  • Keep abreast of the latest developments in the field by continuous learning and pro-actively champion promising new methods relevant to the problems at hand
  • Work with team to make algorithms production quality and scalable
  • Work with Product Management to deliver effective software solutions to our clients business problems


The Qualifications:

  • Experience with designing and implementing machine learning and data mining algorithms in production systems along with the related automated data pipelines
  • Excellent working knowledge and real-life experience implementing machine learning techniques and algorithms including the following:
    • Supervised and unsupervised Machine Learning areas, such Regression, Classification, Clustering and Recommender Systems.
    • Linear and non-linear models - Linear, Lasso, Ridge Regression, Logistic, Multinomial, Ordinal Regression etc.
    • Advanced Machine Learning algorithms - SVM, Random Forest, Gradient Boosting, Neural Networks.
    • Clustering Algorithms - k-means, Hierarchical Clustering etc.
    • Ensemble methods like bagging, boosting and stacking.
    • Feature Engineering
    • Feature Selection techniques Correlation based, model based
    • Understanding of Bias/variance trade-off. Underfitting/Overfitting
    • Dimensionality reduction techniques such as PCA, SVD etc.
  • Comprehensive knowledge of statistics including the following:
    • Resampling techniques Bootstrapping, Cross-validation, Under/oversampling
    • Classic Time Series Algorithms Exponential Smoothing, ARIMA. Ability to detrend and de-seasonalize time series.
    • Residual Analysis
    • Hypothesis testing
    • Monte-Carlo simulation
    • Bayesian Statistics
    • Accuracy Metrics AIC, BIC, AICc, RMSE, MAPE, WMAPE, MAE, ME
  • Experience in data wrangling including
    • Data transformation techniques Normalization, Scaling and Centering, Box-Cox transformation.
    • Anomaly Detection
    • Outlier Adjustments
    • Imputation techniques
    • Data aggregation and disaggregation techniques
  • Experience with demand forecasting for commercial products and related problems like:
    • Hierarchical Forecasting
    • Demand Sensing
    • Temporal Aggregation
    • Diffusion Models
    • Promotion Modeling
    • Intermittent Demand Forecasting
  • MS or PhD in statistics, mathematics, theoretical science, operational research, computer science or related relevant domains
  • Practical knowledge of one or more NoSQL databases
  • R and Python
  • Experience in data visualization
  • Strong communication skills
  • At least three years of professional experience outside academia
  • Strong publication record in top conferences and journal