Senior Principal Scientist/Principal Scientist, Real-World Evidence & Disease Genomics

Sanofi•Cambridge, MA

1d•$148,500 - $214,500•Onsite

About The Position

Join Sanofi's Target, Disease and Systems Biology (TDSB) team and become a key contributor to our Disease Genetics and Genomics cluster. In this role, you will sit at the intersection of real-world evidence generation and disease genomics, leveraging large-scale electronic health records (EHRs) and population biobanks to transform how we understand disease trajectories and evaluate indication expansion opportunities. Working alongside world-class computational and experimental scientists, you will help shape the future of drug discovery and development across Sanofi's therapeutic areas — from early indication prioritization to business development evaluation of external assets. Within our Disease Genetics and Genomics cluster, you'll play a pivotal role in: • Developing and applying cutting-edge EHR-based methods, including foundation models and classical statistical approaches, to generate real-world evidence at scale to understand disease trajectories. • Defining rigorously curated disease cohorts and progression endpoints to support target trial emulation and genomic analyses • Driving Sanofi's engagement with leading population biobanks, including FinnGen and All of Us, to generate insights with direct impact on R&D strategy You will operate in an agile, fast-paced environment with access to industry-leading data infrastructure, working in close collaboration with disease area experts, medical teams, and therapeutic program leads to ensure your work translates into tangible impact on patients' lives. Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions.

Requirements

Ph.D. in Biomedical Informatics, Epidemiology, Computational Biology, Human Genetics, or a related field, with 4+ years of post-PhD experience, preferably in the biopharma or biotech industry
Excellent knowledge of and hands-on experience working with longitudinal EHR datasets and OMOP common data models
Knowledge of target trial emulation methods and causal inference frameworks applied to observational data
Familiarity with GWAS methodology and population-scale genomic analyses
Good knowledge of diseases and medical practices, with the ability to engage meaningfully with clinical and disease area experts
Strong coding skills and demonstrated experience leveraging AI-assisted coding tools such as Cursor or Claude Code to accelerate scientific workflows
Excellent communication skills, with the ability to present complex analytical findings clearly to both scientific and non-scientific stakeholders, and to influence strategic decisions
Genuine enthusiasm for working in an agile, fast-paced team environment where priorities evolve rapidly
Impact-oriented mindset with a strong drive to see scientific work translate into real R&D decisions

Nice To Haves

Experience working with large biobank platforms such as FinnGen, UK Biobank, or All of Us
Experience working in Trusted Research Environments (TREs) or cloud computing platforms (AWS, GCP)
Ability to develop scalable, reproducible analytical pipelines for large-scale data processing
Experience collaborating across cross-functional teams including clinical development, translational medicine, and business development
Experience with agentic AI frameworks and their application to biomedical data analysis or workflow automation

Responsibilities

Lead indication prioritization and expansion for Sanofi R&D assets and external assets by generating target trial emulation from large-scale EHR datasets and biobanks, providing strategic guidance to therapeutic program teams
Develop and implement methods for the analysis of longitudinal medical records, including classical statistical models and EHR foundation models, to evaluate the impact of drugs on disease trajectories through target trial emulation frameworks
Define and champion well-curated disease cohorts and disease progression endpoints using EHRs, working in close coordination with disease area and medical expert teams
Run genome-wide association studies (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 Sanofi's R&D pipeline