Lead quantitative analysis and modeling of real-world data, including CMS, commercial claims, and clinical health data, to generate actionable insights for federal public health. Lead analyses to estimate chronic disease population-level prevalence and incidence leveraging real-world data. Design, implement, and refine machine learning and statistical models (e.g., regression, clustering, causal inference) for surveillance and research purposes. Develop and maintain data pipelines and dashboards for large-scale health datasets using R, Python, and SQL. Utilize DataBricks and Snowflake for scalable data processing and analytics. Collaborate with epidemiologists, clinicians, and public health experts to interpret findings and inform CDC policy and strategy. Prepare scientific reports, presentations, and publications for both technical and non-technical audiences. Ensure data quality, documentation, and reproducibility across all analytic workflows. Support onboarding and training of new team members as needed.