Job Description:
The Observational and Real-World Evidence (CORE) Real-World Data Analytics and Innovation (RDAI) team is seeking a Real-World Data (RWD) Technical Analyst to support real-world evidence generation and oncology outcomes research. This role will work with epidemiologists, biostatisticians, and scientists to conduct analyses using real-world data sources (claims, EHR/EMR, registries) and help develop advanced analytics tools and methodologies that accelerate observational research.
Responsibilities:

• Conduct feasibility analyses using internal real-world datasets (claims, EHR/EMR) to support oncology outcomes research.
• Execute end-to-end study analyses using platforms such as RStudio and SAS Studio.
• Support development and implementation of analytics methods and tools to address confounding in observational healthcare data.
• Perform targeted literature reviews to support study design and methodology.
• Develop and maintain programming documentation, code specifications, and version control.
• Generate analytic outputs and reports supporting real-world evidence studies.
• Collaborate with cross-functional scientists to translate research questions into reproducible analytic workflows.

Requirements:

• Experience working with real-world healthcare data (claims, EHR/EMR, registries).
• Strong understanding of epidemiologic or statistical methods for observational research.
• Proficiency in R, SAS, and SQL (Python a plus).
• Experience with R ecosystem tools (RStudio Workbench, RStudio Connect, RShiny).
• Familiarity with survival analysis methods and packages (e.g., survival).
• Experience working with databases (e.g., Redshift, MySQL).
• Experience with version control tools such as Git.
• Strong documentation, communication, and collaboration skills.
• Experience supporting life sciences or pharmaceutical research environments.