Sr Decision Scientist

CVS Health•New York, NY

1d•$111,240 - $222,480•Remote

About The Position

Aetna Resources, LLC, a CVS Health company, is hiring for the following role in New York, NY: Sr Decision Scientist to develop and implement analytics applications and models to transform data into meaningful information. Duties include: 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; and support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses. Telecommuting available. Multiple positions.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, or a related field
Two (2) years of experience in the job offered or related occupation
One (1) year of experience in Python and R
One (1) year of experience in JIRA and Confluence
One (1) year of experience in Teradata and DB2
One (1) year of experience in MySQL and SQL
One (1) year of experience in Statistical analysis and predictive modeling
One (1) year of experience in Data analytics on large data sets in healthcare, business, or retail sector
One (1) year of experience in Designing data models and solutions for analytical and reporting use cases
One (1) year of experience in Extract/Transform/Load (ETL) processes
One (1) year of experience in Machine Learning or NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP)
One (1) year of experience in 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