Role overview
- 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.
- 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.
- 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.
- 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.
Basic qualifications
- Bachelors and 5+ years of hands-on experience in data science, advanced analytics, or statistical modeling in healthcare, life sciences, or managed care.
- Payor background / clinical understanding (clinical safety, HOS/HRA/BID, etc)
- 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.
Preferred qualifications
- 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.
Tags & focus areas
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