Senior Principal Scientist/Principal Scientist, Real-World Evidence & Disease Genomics
Sanofi
August 19, 2026
Remote friendly (Cambridge, MA)
United States
$148,500 - $214,500 USD yearly
Clinical Research and Development
Main Responsibilities
- Lead indication prioritization and expansion by generating target trial emulation from large-scale EHR datasets and biobanks, providing strategic guidance to therapeutic program teams.
- Develop and implement methods for longitudinal medical record analysis (classical statistical models and EHR foundation models) to evaluate drug impact on disease trajectories via target trial emulation.
- Define and champion well-curated disease cohorts and disease progression endpoints using EHRs, coordinating with disease area and medical expert teams.
- Run GWAS in curated patient cohorts to identify genetic drivers of disease and therapeutic response.
- Apply and scale these methods across large population biobanks (including FinnGen and All of Us) to generate robust, reproducible evidence supporting the R&D pipeline.
Qualifications
Basic Qualifications:
- Ph.D. in Biomedical Informatics, Epidemiology, Computational Biology, Human Genetics, or related field; 4+ years post-PhD (preferably biopharma/biotech).
- Hands-on experience with longitudinal EHR datasets and OMOP common data models.
- Knowledge of target trial emulation and causal inference for observational data.
- Familiarity with GWAS methodology and population-scale genomic analyses.
- Knowledge of diseases/medical practices; ability to engage clinical and disease area experts.
- Strong coding skills; experience using AI-assisted coding tools (e.g., Cursor or Claude Code).
- Excellent communication skills; ability to influence strategic decisions.
- Agile, fast-paced environment mindset; impact-oriented.
- Experience with large biobanks (FinnGen, UK Biobank, All of Us).
- Experience with Trusted Research Environments (TREs) and/or cloud platforms (AWS, GCP).
- Ability to build scalable, reproducible analytical pipelines.
- Cross-functional collaboration experience (clinical development, translational medicine, business development).
- Experience with agentic AI frameworks for biomedical analysis/workflow automation.
Benefits
- Health and wellbeing benefits including high-quality healthcare, prevention and wellness programs, and at least 14 weeks’ gender-neutral parental leave.
- Lead indication prioritization and expansion by generating target trial emulation from large-scale EHR datasets and biobanks, providing strategic guidance to therapeutic program teams.
- Develop and implement methods for longitudinal medical record analysis (classical statistical models and EHR foundation models) to evaluate drug impact on disease trajectories via target trial emulation.
- Define and champion well-curated disease cohorts and disease progression endpoints using EHRs, coordinating with disease area and medical expert teams.
- Run GWAS in curated patient cohorts to identify genetic drivers of disease and therapeutic response.
- Apply and scale these methods across large population biobanks (including FinnGen and All of Us) to generate robust, reproducible evidence supporting the R&D pipeline.
Qualifications
Basic Qualifications:
- Ph.D. in Biomedical Informatics, Epidemiology, Computational Biology, Human Genetics, or related field; 4+ years post-PhD (preferably biopharma/biotech).
- Hands-on experience with longitudinal EHR datasets and OMOP common data models.
- Knowledge of target trial emulation and causal inference for observational data.
- Familiarity with GWAS methodology and population-scale genomic analyses.
- Knowledge of diseases/medical practices; ability to engage clinical and disease area experts.
- Strong coding skills; experience using AI-assisted coding tools (e.g., Cursor or Claude Code).
- Excellent communication skills; ability to influence strategic decisions.
- Agile, fast-paced environment mindset; impact-oriented.
- Experience with large biobanks (FinnGen, UK Biobank, All of Us).
- Experience with Trusted Research Environments (TREs) and/or cloud platforms (AWS, GCP).
- Ability to build scalable, reproducible analytical pipelines.
- Cross-functional collaboration experience (clinical development, translational medicine, business development).
- Experience with agentic AI frameworks for biomedical analysis/workflow automation.
Benefits
- Health and wellbeing benefits including high-quality healthcare, prevention and wellness programs, and at least 14 weeks’ gender-neutral parental leave.