Principal Scientist, AI-Driven Oncology Target Discovery

About the role

We are seeking a highly motivated and innovative Principal Computational Scientist at the intersection of machine learning, agentic AI, and oncology discovery to drive the identification of novel therapeutic targets and resistance mechanisms. In this role, you will integrate multimodal biological, clinical, and real-world datasets to generate actionable insights for target nomination, validation, and portfolio strategy. In partnership with cross-functional teams, you will design and scale advanced analytical platforms and agent-based systems that accelerate decision-making and enhance translational impact across discovery pipelines.

Responsibilities

• Drive integration of computational approaches into cross-functional target discovery workflows, partnering with functional genomics, discovery biology, and computational biology teams to inform target nomination and portfolio decisions.
• Lead the design and deployment of agentic AI and machine learning systems to enable scalable, end-to-end workflows for target identification, prioritization, and validation.
• Integrate and analyze multimodal, patient-derived datasets (omics, functional screens, real-world data) to uncover disease biology, resistance mechanisms, and patient stratification opportunities that inform target selection.
• Translate complex analytical outputs into clear, decision-ready insights to support Go/No-Go recommendations and guide target discovery strategy.
• Author scientific reports and present methods, results, and conclusions to a publishable standard.

Requirements

• Bachelor’s degree and 8+ years of academic/industry experience, or Master’s degree and 6+ years, or PhD and 4+ years.

Qualifications

• Ph.D. in Computational Biology, Systems Biology, Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Deep expertise in computational target identification approaches, including functional genomics, perturbation screens, single-cell and spatial omics, and real-world patient data.
• Demonstrated experience developing and deploying applied AI agents and/or complex LLM-driven applications in research or industry settings.
• Excellent collaboration and leadership skills, with a track record of influencing cross-functional teams and operating effectively in fast-paced, ambiguous environments.
• Strong grounding in systems biology and disease biology within drug discovery, preferably in oncology, with experience translating computational findings into therapeutic hypotheses.
• Proven scientific impact, with a strong publication record in computational biology, machine learning, or bioinformatics, and the ability to communicate complex methodologies and insights effectively.

Pay

Cambridge Crossing: $166,770 – $202,086 (full-time employee basis). Additional incentive cash and stock opportunities (based on eligibility) may be available. Final, individual compensation will be decided based on demonstrated experience.

Benefits

• Health Coverage: Medical, pharmacy, dental, and vision care.
• Wellbeing Support: BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Work-life Benefits:
  • US Exempt Employees: flexible time off (unlimited, with manager approval), 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees).
  • Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays.
  • Based on eligibility: unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs, and an annual Global Shutdown between Christmas and New Year’s Day.