Senior Principal Scientist, Real-World Evidence & Disease Genomics

What you'll do

• Lead indication prioritization for R&D assets using target trial emulation from large-scale EHR datasets.
• Develop methods for analyzing longitudinal medical records to evaluate drug impact on disease trajectories.
• Define and champion well-curated disease cohorts and progression endpoints using EHRs.
• Run genome-wide association studies in curated patient cohorts to identify genetic drivers of disease.
• Scale analysis methods across population biobanks like FinnGen and All of Us to support R&D pipeline.

What we're looking for

• Ph.D. in Biomedical Informatics, Epidemiology, Computational Biology, Human Genetics, or related field with 4+ years of post-PhD experience.
• Expertise in longitudinal EHR datasets and OMOP common data models.
• Knowledge of target trial emulation methods and causal inference frameworks.
• Experience with GWAS methodology and population-scale genomic analyses.
• Strong coding skills and familiarity with AI-assisted coding tools like Cursor or Claude Code.
• Proven ability to work with large biobank platforms such as FinnGen, UK Biobank, or All of Us.
• Demonstrated experience in developing scalable analytical pipelines for large datasets.