Senior Principal Scientist/Principal Scientist, Real-World Evidence & Disease Genomics
Sanofi
July 01, 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 in coordination with disease area and medical experts.
- Run GWAS in curated patient cohorts to identify genetic drivers of disease and therapeutic response.
- Apply and scale methods across population biobanks (e.g., FinnGen, All of Us) to produce robust, reproducible evidence supporting the R&D pipeline.
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 and population-scale genomic analyses.
- Strong coding skills; experience using AI-assisted coding tools (e.g., Cursor, Claude Code).
- Excellent communication skills; ability to influence strategic decisions.
- Experience with biobanks (FinnGen, UK Biobank, or All of Us).
- Experience with Trusted Research Environments (TREs) or cloud platforms (AWS, GCP).
- Ability to build scalable, reproducible analytical pipelines.
Benefits (as stated):
- Health and wellbeing benefits; at least 14 weeks’ gender-neutral parental leave; prevention/wellness programs.
- 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 in coordination with disease area and medical experts.
- Run GWAS in curated patient cohorts to identify genetic drivers of disease and therapeutic response.
- Apply and scale methods across population biobanks (e.g., FinnGen, All of Us) to produce robust, reproducible evidence supporting the R&D pipeline.
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 and population-scale genomic analyses.
- Strong coding skills; experience using AI-assisted coding tools (e.g., Cursor, Claude Code).
- Excellent communication skills; ability to influence strategic decisions.
- Experience with biobanks (FinnGen, UK Biobank, or All of Us).
- Experience with Trusted Research Environments (TREs) or cloud platforms (AWS, GCP).
- Ability to build scalable, reproducible analytical pipelines.
Benefits (as stated):
- Health and wellbeing benefits; at least 14 weeks’ gender-neutral parental leave; prevention/wellness programs.