CVS Health

Position Title/Short Description

Full Text of JOE Listing:

Our Consumer Analytics team provides insights, designs personalized outreaches and nudges, and experiments to educate members on things like staying adherent to medications, avoiding admissions to hospitals, and improving overall health.

What you will do:

Lead the development and standardization of forecasting applications using time series techniques in the service of providing insights to health plans, setting performance guarantees with clients, and driving improved medication adherence with members.

Write complex and efficient code in SQL, Python or R and leverage Exploratory Data Analysis techniques to develop insights from multiple data sources in a cloud environment.

Design, execute, and analyze experiments (e.g., A/B testing, controlled trials) to validate model impact and continuously improve forecasting accuracy and business outcomes.

The ideal candidate:

Has substantial experience applying time series forecasting methods in real-world settings, including model selection, validation, evaluation, and deployment.

Has an in-depth understanding of time series models, including classics like SARIMA, exponential smoothing, time series regressions and machine learning methods like LSTM, XGBoost, etc.

Has a solid grasp of foundations and experience with causal inference methods (e.g., difference-in-differences, synthetic control, instrumental variables) and experimental design.