Principal Scientist, Discovery BioSciences – Integrative New Targets, Oncology
Bristol Myers Squibb
6 days ago
On-site
Cambridge, MA
Clinical Research and Development
Position Summary
- Principal Scientist (Discovery BioSciences) to lead AI/ML for oncology target discovery at the intersection of agentic AI, machine learning, functional genomics, and target discovery.
Position Responsibilities
- Drive high-quality biology-grounded data science to identify new oncology drug development targets.
- Co-develop and execute a multidisciplinary strategy to incorporate AI/ML-derived datasets and validate new target hypotheses.
- Partner with Informatics & Predictive Science to deliver integrative New Target projects and inform large/small molecule inhibitor target modality decisions.
- Develop and implement ML/AI foundation model platforms and algorithms to deliver/validate novel target insights.
- Lead in matrix teams spanning new leads and computational chemistry, genomics, proteomics, and spatial technologies.
Basic Qualifications
- Bachelor’s + 8+ years (academic/industry) OR Master’s + 6+ years OR Ph.D./equivalent in Life Sciences + 4+ years.
Preferred Qualifications / Skills
- On-site at Cambridge, MA (no remote).
- Cancer biology experience: PhD (4+ yrs) or MS (6+ yrs), with strong computational/system/statistical foundations.
- Expertise in functional genomics, single-cell and spatial ‘omics; generating/analyzing genomics/proteomics/functional genomics datasets.
- Required: execute target identification via forward/reverse genetic or phenotypic screens using genome engineering and perturbations (e.g., shRNA, CRISPR, degron tagging).
- Preferred: mechanistic biology that informs drug modality; knowledge of functional oncology targets and cell-surface target modalities (ADC, T-cell engagers, multispecifics, radioligand therapies).
- Strong collaboration/communication; track record (papers/conferences); AI/ML and statistical modeling experience.
Benefits (if eligible)
- Health coverage (medical, pharmacy, dental, vision); wellbeing support; financial protection (401(k), disability, life/accident, supplemental health, travel/personal liability, identity theft, legal support, survivor support).
- Paid time off: flexible/unlimited for US exempt (with manager approval) or specified vacation/holidays for certain roles.
Application Instructions
- If the role is a near match, apply anyway.
- Principal Scientist (Discovery BioSciences) to lead AI/ML for oncology target discovery at the intersection of agentic AI, machine learning, functional genomics, and target discovery.
Position Responsibilities
- Drive high-quality biology-grounded data science to identify new oncology drug development targets.
- Co-develop and execute a multidisciplinary strategy to incorporate AI/ML-derived datasets and validate new target hypotheses.
- Partner with Informatics & Predictive Science to deliver integrative New Target projects and inform large/small molecule inhibitor target modality decisions.
- Develop and implement ML/AI foundation model platforms and algorithms to deliver/validate novel target insights.
- Lead in matrix teams spanning new leads and computational chemistry, genomics, proteomics, and spatial technologies.
Basic Qualifications
- Bachelor’s + 8+ years (academic/industry) OR Master’s + 6+ years OR Ph.D./equivalent in Life Sciences + 4+ years.
Preferred Qualifications / Skills
- On-site at Cambridge, MA (no remote).
- Cancer biology experience: PhD (4+ yrs) or MS (6+ yrs), with strong computational/system/statistical foundations.
- Expertise in functional genomics, single-cell and spatial ‘omics; generating/analyzing genomics/proteomics/functional genomics datasets.
- Required: execute target identification via forward/reverse genetic or phenotypic screens using genome engineering and perturbations (e.g., shRNA, CRISPR, degron tagging).
- Preferred: mechanistic biology that informs drug modality; knowledge of functional oncology targets and cell-surface target modalities (ADC, T-cell engagers, multispecifics, radioligand therapies).
- Strong collaboration/communication; track record (papers/conferences); AI/ML and statistical modeling experience.
Benefits (if eligible)
- Health coverage (medical, pharmacy, dental, vision); wellbeing support; financial protection (401(k), disability, life/accident, supplemental health, travel/personal liability, identity theft, legal support, survivor support).
- Paid time off: flexible/unlimited for US exempt (with manager approval) or specified vacation/holidays for certain roles.
Application Instructions
- If the role is a near match, apply anyway.