Overview In this role you lead the Real World Evidence (RWE) program for a therapeutic area, shaping data-driven strategies to support regulatory objectives. You drive end-to-end non-interventional studies and provide methodological guidance across global teams. You'll engage with health authorities and cross-functional partners to translate real-world data into actionable evidence. This is a high-impact, collaborative role for advancing medicines and patient outcomes in a global, innovative environment.
Compensation / Benefits- health insurance
- PTO
- retirement contributions
- other perquisites
Responsibilities- Act as the functional product lead and SME for assigned studies
- Provide strategic input into drug development plans and Product Integrated Evidence Plans
- Execute the RWE strategy for assigned products and lead studies with minimal supervision
- Present and defend projects at internal boards, governance committees, and senior management meetings
- Identify and select appropriate real-world data sources; drive data strategy for the therapeutic area
- Collaborate with development, regulatory, medical, commercial, market access, and PRWE teams
- Lead Non-Interventional Studies end-to-end: design, planning, protocol development, monitoring, analysis, reporting, dissemination
- Support interactions with health authorities and respond to regulatory requests
- Foster cross-functional collaboration and expand external collaborations with quantitative scientists
Key requirements- PhD or MSc in Epidemiology, Public Health or related field
- 5+ years in health and life sciences or quantitative data sciences
- 5+ years in pharmaceutical/biotechnology industry, CRO, or academic setting
- Experience with studies using secondary data (claims, EMR, registries) across Europe, US, Asia
- Comprehensive expertise in drug development and interfaces with other functions
- Experience with regulatory and payer submissions and interactions
- Familiarity with regulatory standards (ISPE GPP, GVP, ENCePP)
- Excellent oral and written communication
- Collaborative and proactive working style
- Ability to work independently
- Knowledge of federated data networks (CPRD, Optum, IQVIA, TriNetX)
- Experience with OMOP CDM or FHIR data standards
- AI/ML applications in RWE, including NLP
