Decision Scientist

CVS Health•Woonsocket, RI

1d•$98,571 - $144,200•Remote

About The Position

Caremark LLC, a CVS Health company, is hiring for the following role in Woonsocket, RI: Decision Scientist to consult with internal clients to identify opportunities to develop and implement data science solutions to business problems by transforming data into meaningful information. Duties include: apply data mining, data modeling, machine learning, statistical analyses, and predictive and descriptive modeling to extract and manipulate data from multiple large data sources and inform solutions for data science teams; utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data and effectively communicate insights to inform business decisions; compare modeling techniques using statistical performance metrics and recommend improvements; structure data analysis to drive analytics insights and help data scientists determine the best analytical solutions; visualize, interpret, and report data findings to internal clients and leadership; collaborate with business partners to understand requirements and develop statistical analysis and predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes; design and develop data science solutions using industry leading tools, technologies and best practices; and consult on the creation of analytics solutions that effectively weigh business strategy and technical tradeoffs relevant to big data environment. Telecommuting available. Multiple positions.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, Information Systems, or a related field and two (2) years of experience in the job offered or related occupation.
Two (2) years of experience in Data analytics on large data sets in health care, business, or retail sector.
Two (2) years of experience in Domain support for healthcare or retail organization.
Two (2) years of experience in SAS or SQL programming languages.
Two (2) years of experience in Visualization tools, including PowerBI or Tableau.
Two (2) years of experience in Tools to automate CI/CD pipelines: Jenkins, GIT, or Control-M.
Two (2) years of experience in “Big data” platforms including Hadoop (Azure, GCP, or AWS).
Two (2) years of experience in Designing data models and solutions for analytical and reporting use cases.
Two (2) years of experience in Large-scale Spark, Data Warehouse, or Big Data implementation.
Two (2) years of experience in Software Development Life Cycle (SDLC) and best practices.
Two (2) years of experience in Large scale applications development, data science, or data analytics projects.
Two (2) years of experience in Extract/Transform/Load (ETL) processes.
Two (2) years of experience in Designing data architectures, including data pipelines, distributed computing engines, and machine learning infrastructure.
Two (2) years of experience in End-to-end data science lifecycle/workflow.
Two (2) years of experience in Healthcare data management processes and techniques, including data standards, interoperability, and proper data privacy.

Responsibilities

Apply data mining, data modeling, machine learning, statistical analyses, and predictive and descriptive modeling to extract and manipulate data from multiple large data sources and inform solutions for data science teams.
Utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data and effectively communicate insights to inform business decisions.
Compare modeling techniques using statistical performance metrics and recommend improvements.
Structure data analysis to drive analytics insights and help data scientists determine the best analytical solutions.
Visualize, interpret, and report data findings to internal clients and leadership.
Collaborate with business partners to understand requirements and develop statistical analysis and predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes.
Design and develop data science solutions using industry leading tools, technologies and best practices.
Consult on the creation of analytics solutions that effectively weigh business strategy and technical tradeoffs relevant to big data environment.