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in Hoffman Estates, IL

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About this job

JOB SUMMARY:
The Data Scientist is responsible for developing, maintaining and enhancing statistical and machine learning and optimization algorithms to create strategic business opportunities across the organization. This position is constantly challenged to tap into advanced mathematical and statistical techniques to develop scalable solutions. This position is expected to communicate complex concepts clearly.

REQUIRED SKILLS:
* Masters in Statistics , Engineering or Computer Science
* 3-5+ years prior data experience (data preprocessing, Model Development, and presenting results) professionally.
* Experience in economics, statistics, Bayesian statistics, Machine learning, Deep Learning
* Knowledge of various programming software and languages such as, but not limited to R, Stata, Matlab, Python, SQL, and Excel
* Experience in Spark, Scala, Google Cloud,
* Familiarity with version control, especially Git
* Experience in Hadoop-based data tools and languages (e.g. Mahout, Hive, Pig) a plus.
* Sound technical and analytical skills, concise and clean analytic graphics
* Desire and willingness to work in a collaborative, innovative, flexible and team-oriented environment, welcoming push back on conclusions and inferences
* Flexibility, adaptability and the ability to learn quickly in various technical and creative environments, while delivering quality work by tight deadlines
* Ability to perform thorough analysis of complex data, draw sound conclusions, and devise actionable strategies

JOB DUTIES/RESPONSIBILITIES:

  • Develops and utilizes Teradata and Hadoop data pulls (SQL, HIVE, Spark) to produce concise conclusions from raw data in a clean, well- structured and easily maintainable format as well as understand complex business requirements, business goals, and drivers and drive solutions aligning to SHC technology strategy.
  • Designs and Implements mathematical optimization techniques such as stochastic optimization, linear programming, meta optimization and dynamic programming for life of product revenue optimization/ margin optimization and should be able to productionalise in big data platforms such as Spark in Google Cloud.
  • Experience using Probabilistic Programming and uncertainty estimation, Kalman Filter Modeling, Bayesian Statistical Models including Bayesian Hierarchical models, Bayesian Mixed Effect Models, Experience with tools such as Stan and PyMC.
  • Designs and Implements A/B testing and uses the new information to update knowledge database. Familiar with techniques such as difference in difference testing etc.
  • Implements Time Series Models, evaluates forecast accuracy, computes seasonality, and applies approaches that are robust to sparse time series.
  • Implements latest advanced scalable statistical/machine learning forecasting models using Tensorflow and uses the concepts such as category embedding and Recurrent Neural Networks to achieve higher forecasting accuracy.
  • Designs and implements Dynamic Pricing models such as Bayesian Bandit, Thomson Sampling, UCB. Must also have experience in Reinforcement Learning.
  • Designs, implements and automates modeling and analysis procedures on existing and experimentally created data using open source programs including but not limited to Python and R..
  • Experience with scientific and computing packages in R, Python such as H2O, Spark MlLib, glmnet, rstan, xgboost, caret, SkLearn, statsmodels
  • Plans for integrating new systems, provides leadership for service-oriented architecture (SOA) programs and adoption, and assesses the risk of implementing new solutions. Oversees and creates solutions implemented on large data warehouses. Provides leadership in developing robust solutions for Analytics, Predictive Analytics, Pattern Recognition, Data Mining, Reporting, Web Analytics, and Metadata Management.
  • Organizes conclusions drawn from data into action items to improve pricing strategy and presents conclusions and action items to BU partners and pricing leadership.
  • Provides insight into emerging technology and provide direction in the incorporation of new technology. Creates enhancements and defect resolution on an ongoing basis to improve efficiency of the code base, as well as conduct POCs (Proof of Concept) to evaluate new technologies when required.
  • Establishes reporting and tracking to continuously monitor and report out impact
  • Increases pace and confidence of learning by combining state of the art technology and statistical methods (parametric and non- parametric econometrics and machine learning); provides expertise in integrating advanced analytics into ongoing business processes (combine data mining techniques with structure approaches to avoid spurious correlations). Maintains awareness of modeling and analytics best practices from a wide range of industries


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