Senior/Principal ML Scientist, Translational Biology
Core
Build systems to assess mechanistic support for clinical programs by analyzing human genetic, multi-omic, and trial-derived evidence to determine if an intervention's proposed mechanism is established, active, and rate-limiting in patient populations.
Role type
Senior/Principal ML Scientist (Translational Biology)
Builds
Automated assessment systems for clinical program mechanisms, outcome-verifiable forecasts of program progression, and structured evidence evaluations.
Domain
Biomedicine / Translational Medicine / Clinical Development
Deliverable
production ML models
Required skills
Python, human genetic data analysis, multi-omic data analysis, cohort data analysis, trial-derived evidence analysis, mechanistic reasoning about therapeutic interventions, clinical trial design fluency, evidence judgment, reproducible pipeline construction
Preferred skills
human genetics for target identification, biomarker development, patient stratification, clinical trial datasets analysis, language model evaluation, survival analysis, structured evidence frameworks (GRADE)
Technologies
Python
Responsibilities
Build systems to assess mechanistic support for clinical programs; Analyze human genetic, expression, cohort, and trial-derived evidence to determine mechanism presence and activity; Evaluate trial design (endpoints, biomarkers, eligibility) against proposed mechanisms; Build outcome-verifiable forecasts of program progression; Co-design systems with scientists and engineers; Publish findings on predictability from mechanistic and human evidence.
Seniority
Senior/Principal, hands-on IC with strategy & mentorship
