Develop ML/AI models that support discovery workflows, including target prioritization, multi-omics integration, and mechanistic inference
Job Summary
Develop ML/AI models that support discovery workflows, including target prioritization, multi-omics integration, and mechanistic inference.
Design, build, and maintain robust data pipelines that curate, standardize, and integrate diverse R&D datasets.
This is a rare opportunity to grow in one of the world’s most ambitious and fastest-growing Pharma R&D Data Science organizations, shaping how TD data powers next-generation therapies.
Matching Summary
Develop ML/AI models that support discovery workflows, including target prioritization, multi-omics integration, and mechanistic inference.
Salary
Base: $117,000.00 - $201,250.00; Bonus/Equity: Not specified; Benefits: Vacation, Sick time, Holiday pay, Work/Personal/Family Time, Parental Leave, Bereavement Leave, Caregiver Leave, Volunteer Leave, Military Spouse Time-Off
Skills & Requirements
Must-have
Machine Learning/AI models
Python programming
Data engineering pipelines
Cloud computing environments
Drug discovery lifecycle
Nice-to-have
Pharma/biotech discovery experience
Omics/imaging/assay data
Data standards (FAIR, ontologies)
Regulated environments
Key Requirements
Master's or Ph.D. in related field
Experience applying ML/AI in scientific domains
Experience with scientific/ML libraries
Practical experience with data engineering
Ability to work directly with experimental scientists