Sr. Data Scientist – Computational Drug Discovery
$87,222–$117,947 year
On-site · Burnaby, British Columbia, Canada
Job Summary
Sr. Data Scientist – Computational Drug Discovery at Amgen leads molecular dynamics and machine learning initiatives to enable large-molecule therapeutic discovery. The role designs and executes MD simulations (including enhanced-sampling and kinetics-focused approaches) to study protein structure, dynamics, and interactions; builds ML models leveraging molecular simulation, sequence, structure, and experimental data to predict properties and prioritize designs; develops integrated multi-modal modeling frameworks; incorporates physics-based insights into ML models for better interpretability; develops scalable, reproducible computational workflows; mentors junior scientists; collaborates with structural biology, protein engineering, and experimental teams; evaluates emerging ML/molecular simulation methods to enhance the computational discovery toolkit; strong emphasis on communicating findings through publications and technical docs. The position expects PhD (or equivalent) in computational sciences or related fields, with deep expertise in MD, ML, and software tools, and experience in cross-functional collaboration within biologics discovery.
Required Qualifications
- PhD in Computational Biology, Computational Chemistry, Theoretical Chemistry, Biophysics, or related field OR Master’s degree with 3 years of related experience OR Bachelor’s degree with 5 years of related experience
- Postdoctoral or equivalent research experience in molecular simulation, computational biophysics, or AI-accelerated drug discovery (preferred)
- Deep expertise in molecular dynamics simulations of biomolecular systems, including enhanced sampling, rare-event methods, free-energy or kinetics analysis, and interpretation of conformational ensembles (preferred)
- Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch) and molecular simulation / modeling software (GROMACS, OpenMM, Amber, NAMD)
- Experience deriving ML features from molecular simulation trajectories and integrating with sequence/structure/experimental data
- Experience with large-scale datasets and HPC/cloud platforms (e.g., AWS)
- Experience implementing reproducible scientific computing practices (git, Docker, workflows)
- Strong scientific communication and publications
- Ability to influence cross-functional teams by translating computational results into actionable recommendations
- Experience supporting biologics or large-molecule therapeutic discovery (strongly preferred)
Apply with one swipe on Sorce. We auto-fill applications and apply on your behalf — no cover letters, no 40-minute forms.
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.