Data Scientist

CVS Health•Woonsocket, RI

4d•$98,571 - $158,620•Hybrid

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Caremark, LLC., a CVS Health company, is hiring for the following role in Woonsocket, RI: Data Scientist to develop and implement analytics applications and models to transform data into meaningful information.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Data Science, Business Analytics, Statistics, Mathematics, or a related field and one (1) year of experience in the job offered or related occupation.
Programming in Java, Python, or R
XML, JSON, HTML, CSS, or JavaScript
Oracle
MySQL
SAS or SQL programming languages
Visualization tools, including PowerBI
Machine learning, statistical analysis and predictive modeling
NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP)
Contributing to largescale applications development, data science, or data analytics projects
Data analytics on large data sets in healthcare, business, or retail sector
Feature engineering, model training, hyperparameter tuning, distributed model training, and supervised and unsupervised learning implementation
Quantitative analysis techniques, including clustering, regression, and pattern recognition.

Responsibilities

Design and develop data solutions using industry leading tools, technologies and best practices to profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business.
Develop advanced algorithms and statistical predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes.
Utilize data mining, data modeling, natural language processing, and machine learning to extract and manipulate data from multiple large data sources and deliver predictive models that inform solutions for in-house teams (i.e. pharmacy pricing, medical costs, risk scores, onboarding) and customer engagement across critical journeys (i.e. calories, heart rate, breast cancer, maternity).
Utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems.
Visualize and interpret data and create reports, manipulate data using statistical software, and compare models using statistical performance metrics.
Support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses.