Principal Data Scientist

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Role Overview Aetna, a CVS Health company, is a leading health innovation organization focused on transforming healthcare delivery and improving outcomes. As part of the growing Medicare Stars organization, we are seeking a Principal Data Scientist to lead advanced analytics, forecasting, and scientific modeling efforts that drive enterprise-level Star Ratings performance.

This role is a senior individual contributor and thought leader responsible for defining and scaling the next generation of Stars forecasting, cutpoint analytics, and performance modeling. The individual will lead development of predictive models, statistical frameworks, and AI-enabled analytics solutions to inform strategic decision-making across Medicare Stars domains.

This position will own end-to-end analytic strategy-from data engineering and model design to executive insights and business impact-and will serve as a key partner to leadership across Product, Clinical, Quality, and Data organizations.

Position Summary Strategic Leadership & Analytics Lead the design and execution of enterprise-level Medicare Stars forecasting models, including multi-year projections (e.g.,  stars scenarios).Define scientific frameworks for Stars cutpoint derivation, incorporating CMS methodology, guardrails, and national distribution analysis.

Partner with senior leadership to translate forecast insights into actionable business strategies and risk mitigation plans.

Provide thought leadership in Stars performance analytics, influencing roadmap, prioritization, and investments.

Advanced Modeling & Forecasting:
Develop and maintain end-to-end forecasting models across domains: CAHPS, HEDIS, HOS, Patient Safety / Pharmacy measures

Build year-end projections based on historical trends, seasonality, and industry benchmarks.

Perform sensitivity analysis and scenario modeling (Low/Mid/High models) to quantify risk and opportunity.

Design predictive models leveraging statistical methods, machine learning, and time-series forecasting.

Translate regulatory changes into model enhancements and impact assessments.

Lead efforts to interpret and operationalize CMS technical guidance (e.g., disaster adjustments, guardrails, cutpoint methodology).Experience in building year-end forecasts using historical trends and industry benchmarks

Data, Technology Leadership & Technical Skills Architect and implement scalable analytics solutions using:

Snowflake (Snowpark, data pipelines, governance)
Python / SQL-based modeling frameworksML/AI and LLM-enabled analytics (including RAG architectures)
Build integrated data ecosystems combining:

Structured clinical and operational data Survey and experience data (CAHPS/HOS)
External industry benchmarks

Data Visualization:
Ability to create compelling visualizations using tools like Tableau, Power BI, and Snowflake and any other BI tools

Author Snowpark/Python/SQL transformations, Streams & Tasks, and job orchestration to enable near-real-time and batch analytical workloads.

Strong expertise in:
Time-series forecasting, Machine learning & predictive modeling and Statistical inference and simulation modeling

Database Management:
Knowledge of SQL and No

SQL databases for efficient data storage and retrieval.

Enable self-service analytics and executive dashboards for real-time decision support.

Provide technical leadership and mentorship to data scientists and analysts.

Integrate Snowflake with LLMs (OpenAI or equivalent) for tasks such as summarization, question-answering, classification, and code-generation-using External Functions, Snowpark, and/or secure API patterns.

Establish best practices for modeling, validation, documentation, and version control.

Ensure compliance with data governance, privacy, and…