Principal Scientist, AI-Driven Oncology Target Discovery
Bristol Myers Squibb
August 30, 2026
Remote friendly (Cambridge, MA)
United States
Clinical Research and Development
Summary
We seek a Principal Computational Scientist (machine learning, agentic AI, oncology discovery) to identify novel therapeutic targets and resistance mechanisms by integrating multimodal biological, clinical, and real-world datasets.
Key Responsibilities
- Integrate computational approaches into cross-functional target discovery workflows; partner with functional genomics/discovery biology/computational biology to inform nomination and portfolio decisions.
- Design and deploy agentic AI and machine learning systems for scalable, end-to-end target identification, prioritization, and validation workflows.
- Integrate/analyze multimodal patient-derived datasets (omics, functional screens, real-world data) to uncover disease biology, resistance, and patient stratification.
- Convert analytic outputs into decision-ready insights for Go/No-Go recommendations and discovery strategy.
- Author publishable scientific reports and present methods/results.
Basic Qualifications
- Bachelor’s + 8+ years (academic/industry)
- OR Master’s + 6+ years (academic/industry)
- OR PhD + 4+ years (academic/industry)
Preferred Qualifications / Skills
- PhD in Computational Biology, Systems Biology, Computer Science, Machine Learning, Statistics, or related field.
- Expertise in computational target identification (functional genomics, perturbation screens, single-cell/spatial omics, real-world patient data).
- Experience developing/deploying applied AI agents and/or LLM-driven applications.
- Strong collaboration/leadership in fast-paced, ambiguous environments.
- Systems biology/disease biology grounding in drug discovery (preferably oncology) and translation to therapeutic hypotheses.
- Publication record and ability to communicate complex methods.
Compensation (range)
- Cambridge Crossing: $166,770–$202,086
Benefits / Work-life (selected)
- Health coverage; wellbeing support; 401(k); disability/life/insurance offerings.
- Paid time off (role/location dependent), plus possible additional time-off eligibility.
Application Instruction
- Encourage to apply even if the resume doesn’t perfectly match the role.
We seek a Principal Computational Scientist (machine learning, agentic AI, oncology discovery) to identify novel therapeutic targets and resistance mechanisms by integrating multimodal biological, clinical, and real-world datasets.
Key Responsibilities
- Integrate computational approaches into cross-functional target discovery workflows; partner with functional genomics/discovery biology/computational biology to inform nomination and portfolio decisions.
- Design and deploy agentic AI and machine learning systems for scalable, end-to-end target identification, prioritization, and validation workflows.
- Integrate/analyze multimodal patient-derived datasets (omics, functional screens, real-world data) to uncover disease biology, resistance, and patient stratification.
- Convert analytic outputs into decision-ready insights for Go/No-Go recommendations and discovery strategy.
- Author publishable scientific reports and present methods/results.
Basic Qualifications
- Bachelor’s + 8+ years (academic/industry)
- OR Master’s + 6+ years (academic/industry)
- OR PhD + 4+ years (academic/industry)
Preferred Qualifications / Skills
- PhD in Computational Biology, Systems Biology, Computer Science, Machine Learning, Statistics, or related field.
- Expertise in computational target identification (functional genomics, perturbation screens, single-cell/spatial omics, real-world patient data).
- Experience developing/deploying applied AI agents and/or LLM-driven applications.
- Strong collaboration/leadership in fast-paced, ambiguous environments.
- Systems biology/disease biology grounding in drug discovery (preferably oncology) and translation to therapeutic hypotheses.
- Publication record and ability to communicate complex methods.
Compensation (range)
- Cambridge Crossing: $166,770–$202,086
Benefits / Work-life (selected)
- Health coverage; wellbeing support; 401(k); disability/life/insurance offerings.
- Paid time off (role/location dependent), plus possible additional time-off eligibility.
Application Instruction
- Encourage to apply even if the resume doesn’t perfectly match the role.