Role overview
The Senior Data Scientist, Clinical Data Science (HOS & HRA) plays a key role in advancing analytics that improve Medicare Advantage member outcomes and CMS Star Ratings performance. This position supports the design, implementation, and automation of analytic solutions for the Health Outcomes Survey (HOS) and Health Risk Assessment (HRA) programs—two core domains in Aetna’s Medicare clinical strategy.
The ideal candidate combines strong technical depth in data science and statistical modeling with the ability to translate complex findings into actionable insights for non-technical audiences. This individual will automate recurring data science workflows, conduct robust impact and descriptive analyses, and collaborate closely with clinical, quality, and operations teams to identify emerging opportunities that improve member experience and population health outcomes.
*Key Responsibilities
Clinical Data Science & Analytics**
- Lead the development of analytic models and descriptive frameworks supporting HOS and HRA performance improvement across Medicare Advantage.
- Conduct impact analyses, trend identification, and segmentation to explain drivers of performance and inform strategy.
- Automate recurring analytics and reporting pipelines to increase reliability, efficiency, and reproducibility of insights.
- Apply advanced statistical, predictive, and causal inference methods to evaluate intervention effectiveness and identify member-level opportunities.
- Develop and refine tools for data visualization and storytelling to communicate results clearly to non-technical stakeholders.
- Partner with business leaders to translate analytic results into actionable recommendations for program design, member outreach, and care interventions.
What we're looking for
- Master’s (2-3yrs) or PhD in Data Science, Statistics, Epidemiology, Public Health, or a related quantitative field.
- Familiarity with Medicare Advantage, CMS Star Ratings methodology, and clinical quality measures.
- Experience working within modern cloud environments (e.g., Google Cloud Platform, Databricks) and with workflow orchestration tools (Airflow, dbt).
- Background in impact measurement, causal inference, or time-series analysis in healthcare contexts.
Interview process
Auth
: GC/USC so client has ability to convert without sponsorship
- Analytic Excellence: Strong applied modeling, statistical, and automation skills.
- Storytelling with Data: Ability to distill technical insights into clear, actionable narratives.
- Collaboration: Effective partner to clinical, operations, and business teams.
- Innovation: Continuously improves processes, tools, and methods for scale and efficiency.