Clinical Data Scientist​/Methodologist

Job Title:

Clinical Real World Data Scientist/Methodologist

Location:

US – Bridgewater / Morristown

Join the team protecting half a billion lives every year with next‑gen science, mRNA innovation, and AI‑driven breakthroughs. In Vaccines, you’ll help advance prevention on a global scale and shape the future of immunization. The Data Assessment Center of Excellence (CoE) is a specialized team within Sanofi’s Digital RWD & HI function, operating at the intersection of epidemiology, RWD, data products and insights/evidence generation.

The vision of the CoE is to ensure all Sanofians have the right data, used the right way, for real patient impact.

Sanofi is an R&D‑driven, AI‑powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system and innovative pipeline enables us to invent medicines and vaccines that treat and protect millions of people around the world.

• Design and evaluate methodology to assess the fitness‑for‑purpose of real‑world data (RWD) sources for insights or evidence generation.
• Support the development of reliable RWD Foundation and products.
• Lead feasibility assessments for RWD sources (electronic health records, administrative claims, patient registries, wearable/digital health data) to determine suitability for specific research/business objectives.
• Develop and apply structured data assessment frameworks to evaluate data quality dimensions, including accuracy, completeness, validity, timeliness, longitudinal consistency, and integrity.
• Assess the availability and representativeness of patient populations within RWD sources for internal decision‑making and regulatory‑grade evidence generation.
• Evaluate feasibility of extracting structured and unstructured data elements (e.g., clinical scores, patient‑reported outcomes) from EHR systems, including NLP‑based extraction from clinical notes.
• Document assessment outcomes in standardized feasibility reports and communicate findings clearly to cross‑functional stakeholders.
• Identify and articulate limitations of RWD sources, such as proxy endpoint constraints and population coverage gaps.
• Design methodologically sound recommendations and minimize misuse of RWD, ensuring reliable, trustworthy, and timely insights or evidence.
• Ensure appropriate use of ICD codes, procedure codes, and other medical coding standards for patient identification, healthcare provider segmentation, clinical site identification, and phenotyping.
• Apply advanced epidemiological and biostatistical methods, including propensity score methods, time‑to‑event analyses, sensitivity analyses, and bias assessment.
• Provide methodological input on the use of clinical score proxies and surrogate endpoints in RWD contexts, delineating applicability for internal versus regulatory/publication use.
• Provide methodology advice ensuring deliverables from RWD Foundation, RWD Science, and RWD Products are based on medical evidence/guidelines, clinically and contextually relevant.
• Work closely with analysts and data scientists to ensure methodological recommendations are realistic and implementable.
• Partner with R&D, Business units (Vaccines, General Medicine and Specialty Care) and Digital teams on data identification and appropriate usage of RWD across the drug lifecycle.
• Serve as the methodological point of contact for fit‑for‑purpose data assessment inquiries from internal stakeholders.
• Collaborate with RWD Foundation, RWD Product Owners, and RWD Data Sciences to ensure RWD is used appropriately to inform reliable decision‑making and provide knowledge transfer on data domain expertise.
• Manage external data vendors and technology partners (e.g., EHR, claims, registries) to understand data limitations and verify methodological recommendations when required.

• Advanced degree (Master's or PhD) in Epidemiology, Biostatistics, Health Informatics, Health Economics, Pharmacoepidemiology, or a closely related quantitative discipline.
• Minimum 4‑5 years (Master’s) or 2‑4 years (Doctoral) of relevant experience in real‑world data, commercial analytics, real‑world evidence,…