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Clinical Data Scientist/ Methodologist
- Bridgewater, Virginia, United States
- Bridgewater, Virginia, United States
Über
US Bridgewater / Morristown
About the Job 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.
The Clinical RWD Scientist/Methodologist is a critical role within the Data Assessment Center of Excellence (CoE), embedded in Sanofi’s Digital RWD & HI function. This role bridges the gap between theoretical concepts to practical & reliable RWD solutions. You are an agile professional interested with deep subject matter expertise in US RWD, pharmaco-epidemiological methods and a quick learner of new data, methodology, and technology. You are a proactive team member that values cross-learning, sees challenges as opportunity and can work with assumptions.
About Sanofi We’re 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. Together, we chase the miracles of science to improve people’s lives.
Main Responsibilities You will be responsible for designing the methodology to evaluate the fitness-for-purpose of real‑world data (RWD) sources for insights or evidence generation, support the development of reliable RWD Foundation and Products. This role serves as a methodological authority and RWD data domain expert, ensuring best‑in‑class data selection and optimal data usage to generate reliable insights or evidence to better understand gaps in patient care and healthcare provider involvement. This role is key to ensure data‑driven decisions are reliable, trustworthy, and timely.
Data Assessment & Fitness-for-Purpose Evaluation
Lead and execute 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 available in Sanofi for both internal decision‑making and regulatory‑grade evidence generation
Evaluate the 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, population coverage gaps
Methodological Design & Optimal RWD Usage
Design methodologically sound recommendations & minimize misuse of RWD, leading to unreliable insights or evidence generation
Ensure appropriate use of ICD codes, procedure codes, and other medical coding standards (sourced from peer‑reviewed references such as PubMed, Embase, and Orphanet, etc.) 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, clearly delineating their applicability for internal versus regulatory/publication use
Provide methodology advises ensuring deliverables from RWD Foundation, RWD Science, and RWD Products are based on medical evidence/guidelines, clinically & contextually relevant
Work closely with analysts & data scientists to ensure methodological recommendation is realistic and implementable
Cross‑Functional Collaboration & Stakeholder Engagement
Partner with R&D, Business units (Vaccines, General Medicine and Specialty Care) & Digital teams on data identification and appropriate usage of RWD for insights / evidence generation across 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, RWD Data Sciences to ensure RWD are used appropriately to inform reliable decision making & to provide knowledge transfer on data domain expertise
Manage external data vendors and technology partners (e.g., EHR, claims, registries) to understand data limitations and to verify methodological recommendations when required
NOTE: This role does not conduct real‑world evidence studies.
About You Qualifications
Advanced degree (Master’s or PhD) in Epidemiology, Biostatistics, Health Informatics, Health Economics, Pharmacoepidemiology, or a closely related quantitative discipline
Minimum 4–5 years for Masters degree holder or 2–4 years for Doctoral degree holder of relevant experience in real‑world data, commercial analytics, real‑world evidence, health outcomes research, fit‑for‑purpose feasibility assessment, data quality assessment or a related field within the pharmaceutical, biotech, or health technology industry
Experience in predictive modeling using RWD to identify at‑risk patient populations with a publication record in peer‑review journals
Experience in patient & healthcare provider segmentation to inform Medical and Commercial strategy
Demonstrated expertise in epidemiological study design and statistical methods such as propensity score matching, descriptive statistics, regression analysis, predictive modelling
Strong proficiency in statistical programming languages: SQL, Python, R, and/or SAS
Solid working knowledge of Snowflake for database querying and data extraction
Familiarity with medical coding systems: ICD‑10, CPT, SNOMED CT, LOINC, RxNorm and experience/knowledge of the OHDSI OMOP CDM standardized data model for healthcare data
Understanding of US EHR, claims, disease registry data, public health surveillance data as well as US healthcare billing system
Experience with AI coding tools such as Cursor, GitHub Copilot, Claude, LLM
Knowledge of automation tools such as Power Automate, Power App (an asset not required)
Requires a high level of interactive communication with diverse stakeholders
Can work with assumptions & in a fast‑paced environment
Proven teamwork and collaboration skills
Why Choose Us?
Bring the miracles of science to life alongside a supportive, future‑focused team.
Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
Enjoy a thoughtful, well‑crafted rewards package that recognizes your contribution and amplifies your impact.
Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high‑quality healthcare, prevention and wellness programs and at least 14 weeks gender‑neutral parental leave.
Join the digital force behind Sanofi’s AI‑powered pipeline, where Expert, Generative, and Snackable AI accelerate the discovery, development and delivery of breakthrough treatments to patients.
Help reduce time from discovery to commercialization, delivering life‑changing medicines to patients faster than ever.
Benefit from pioneering partnerships with OpenAI, AQEMIA, IBM, and others.
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affiliated Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in company employee benefit programs, and additional benefits information can be found here.
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Sprachkenntnisse
- English
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