Senior Decision Scientist - Growth Analytics - cvshealth

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.

Position Summary

Do you want to drive the next level of growth for a leading national B2C healthcare brand, impacting millions of prospects and members? We’re seeking innovative leaders to accelerate growth in Aetna’s Medicare Business by leveraging consumer marketing, sales, and product design powered by data science and consulting expertise.

Our Medicare Analytics team is integral to Aetna’s go-to-market strategies, including growth planning, business case development, customer segmentation, product design, media mix optimization, attribution modeling, and member retention. Using advanced machine learning techniques and petabytes of data, we infuse analytics into every aspect of our growth initiatives.

You’ll help us shape the future by solving complex problems, driving quantitative analysis, and delivering data-driven insights that power tomorrow’s business innovations.

Key Responsibilities

Work closely with our Marketing and Sales partners to inform Aetna’s Medicare member growth strategy through analytics – e.g., customer segmentation, test design, forecasting, what-if scenarios, and more

Design and document end-to-end ML system architecture, from data ingestion and feature engineering to model serving and front-end consumption

Leverage AI tools and techniques to understand model input/output/performance and inform development cycles

Build and test prototypes quickly to enable rapid iteration and experimentation

Collaborate with engineering and product teams to ensure models are production-ready and integrated effectively

Provide technical leadership and review on architecture decisions across the ML lifecycle

Required Qualifications

3+ years of professional experience in data analytics, machine learning, BI, data engineering, or applied data science

3+ years of experience using with SQL and Python/R for data analysis

2+ years of experience using statistical techniques on complex data to solve business problems

Proven track record of leveraging data to influence cross-functional stakeholders, partners, and leadership to drive decisions

Ability to clearly articulate and communicate complex problems and solutions in a simple, logical, and impactful manner

1+ years of experience with data visualization tools such as Tableau, R Shiny, or Power BI

1+ years of demonstrated ability to manage relationships with technical and non-technical stakeholders

Preferred Qualifications