Data Scientist Real World Evidence

## About the role As a Data Scientist, Real-World Evidence, you will sit at the intersection of analytics, science, and customer delivery. This is a hands-on role. You will work directly with real-world clinical datasets, own analytic workflows end to end, and ensure every customer-facing dataset and analysis meets a high standard of quality and reproducibility. ## Data Delivery + Quality Control - Prepare customer-ready analytic datasets from real-world clinical data, including EHR and other healthcare sources. - Perform rigorous data QA to validate cohort definitions, variable construction, and derived endpoints. - Write and complete QC reports documenting validation checks and delivery specifications. - Partner with engineering to identify and resolve data inconsistencies or pipeline issues. - Ensure reproducibility and clear documentation of all analyses. ## Feasibility + Commercial Analytics - Generate patient counts and feasibility analyses based on diagnosis, therapies, labs, procedures, biomarkers, and inclusion or exclusion criteria. - Build cohort attrition tables and summary statistics to support business development and customer proposals. - Deliver rapid, reliable analyses to answer prospective partner questions. ## Real-World Evidence Studies - Design and execute observational analyses using real-world data. - Apply appropriate statistical methods to address confounding, bias, and missing data. - Produce clear tables, figures, and summaries for external audiences. - Contribute to white papers, study reports, and methods documentation. - Translate complex findings into clear, actionable insights for both technical and non-technical stakeholders. The first step will be a take home assignment to showcase your coding and analytical skills