Sr. Data Scientist

Job Description 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. 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. Collaboration & Consultation • Serve as a bridge between technical and non-technical teams, ensuring analytic outputs are interpretable and actionable. • Collaborate cross-functionally with Clinical Operations, Member Experience, and Quality teams to align analytics with enterprise goals. • Support enterprise data modernization and automation initiatives by identifying repeatable use cases for scalable analytics and workflow improvement. • Mentor junior data scientists and analysts on best practices for data integrity, modeling, and automation. Technical & Operational Excellence • Design and maintain automated analytic processes leveraging Python, SQL, and modern cloud environments (e.g., GCP). • Ensure accuracy, consistency, and explainability of models and metrics through disciplined version control and validation. • Contribute to the team’s continuous improvement culture by recommending new methods, tools, or data sources that enhance analytic precision and speed. Required Skills & Experience • 5+ years of hands-on experience in data science, advanced analytics, or statistical modeling in healthcare, life sciences, or managed care. • Strong proficiency in Python, SQL, and data science libraries (e.g., pandas, scikit-learn, statsmodels). • Demonstrated ability to automate data workflows and standardize recurring analyses or reporting. • Experience applying statistical and descriptive analytics to clinical or quality measurement problems (e.g., HOS, HRA, CAHPS, or HEDIS). • Proven success communicating complex findings to non-technical business partners and influencing decision-making. • Ability to work effectively in a fast-paced, cross-functional environment. Nice to Have Skills & Experience • Master’s 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.