Principal Scientist, Computational Biology

Principal Scientist, Computational Biology

Location:

Cambridge, MA (no remote option).

• Perform computational research and integrative analyses on multimodal biological profiling datasets (e.g., transcriptomic, proteomics, single‑cell omics, spatial profiling) to support early pipeline programs.
• Apply machine learning and other advanced computational/statistical approaches to compare high‑dimensional experimental readouts from perturbation experiments/screens (e.g., CRISPR screens, perturb‑seq, cellular imaging) to disease states defined by patient data and contribute to target nomination and validation for neuro‑, cardiovascular, and autoimmune disease indications.
• Collaborate with external partners in industry, academia, and pre‑competitive collaborations (e.g., NIH Accelerating Medicines Partnership) on novel computational and experimental approaches.
• Communicate findings and recommend follow‑up actions in multiple settings (including 1:1, seminars, and team meetings).

• Bachelor’s degree in computational biology, computational genomics/genetics, computer science, statistics, mathematics, or related discipline plus 8+ years of academic or industry experience.
• Master’s degree in the same fields plus 6+ years of academic or industry experience.
• PhD in the same fields plus 4+ years of academic or industry experience.

• Advanced hands‑on knowledge of a high‑level programming language such as R or Python and reproducible research practices.
• 5+ years of post‑graduate experience in computational biology research (biopharma industry preferred) with a track record (e.g., scientific publications) in driving and advancing research projects or programs.
• Hands‑on experience analyzing and integrating high‑dimensional molecular datasets such as multi‑omics (RNA‑seq, ATAC‑seq, proteomics, ChIP‑seq/CUT&RUN), single‑cell (CITE‑seq, scATAC‑seq, perturb‑seq).
• Hands‑on experience with spatial profiling (Xenium, Visium, Geo Mx, CosMX) data analysis and interpretation.
• Experience implementing or developing statistical methodologies and machine learning algorithms applied to biological problems.
• Background in human disease biology, especially neurodegenerative, cardiovascular, or autoimmune diseases strongly preferred.
• Experience applying computer vision models to cellular imaging data preferred.
• Experience utilizing AI agents such as claude coding to accelerate workflow preferred.
• Scientific curiosity with an ability for self‑learning.
• Strong oral and written communication skills.

Cambridge Crossing: $166,770 - $202,086.

Additional incentive cash and stock opportunities (based on eligibility) may be available. Final individual compensation will be determined based on demonstrated experience.

• Health Coverage: Medical, pharmacy, dental, and vision care.
• Well‑being Support: Programs such as 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.

• 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).
• 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.
• Additional time off may include 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 Years Day.

Bristol Myers Squibb is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, pregnancy, marital status, gender expression, genetic information, political affiliation, or any other characteristic protected by law.

We will never request payments, financial information, or social security numbers during our application or recruitment process.

Qualified applicants with arrest and conviction records will be considered for employment pursuant to applicable laws.