Lead, Computational Sciences - Biotherapeutics Portfolio

Biopharma Careers; Virginia (MN); Hybrid; USD 184,000 - 257,000; Full time

Benefits offered by this job

Wellbeing support

Retirement and financial protection

11 paid company holidays

Job summary

Bristol Myers Squibb seeks an experienced leader to direct a computational sciences team supporting antibody discovery, design, and decision-making across oncology, neuroscience, and immunology programs.

You will set priorities, mentor scientists, and ensure computational work informs go/no-go decisions from binder discovery through candidate nomination, driving high-impact portfolio outcomes.

Qualifications

• Bachelor's degree with 12+ years of academic/industry experience or Master's with 10+ years or PhD with 8+ years.
• Advanced degree in computational biology/chemistry/engineering/biophysics or related field preferred.
• 4+ years of leadership experience.
• Experience influencing project decisions through analysis and clear communication.

Responsibilities

• Lead a computational sciences portfolio team across biologics programs in pre-clinical pipeline.
• Apply bioinformatics, ML, and AI-enabled design to improve antibody selection and design.
• Define when computational predictions are reliable and when additional experiments are needed.
• Partner with project teams to translate questions into computational strategies and clear recommendations.
• Communicate hypotheses, methods, results, and recommendations to project teams and governance forums.
• Coach and develop computational scientists, fostering rigor, urgency, accountability, collaboration, and impact.

Skills

Bioinformatics

Machine learning

AI-enabled design

Education

PhD with 8+ years

MS with 10+ years

BS with 12+ years

Job description

Bristol Myers Squibb seeks an experienced leader to direct a computational sciences team supporting antibody discovery, design, and decision-making across oncology, neuroscience, and immunology programs.

You will set priorities, mentor scientists, and ensure computational work informs go/no-go decisions from binder discovery through candidate nomination, driving high-impact portfolio outcomes.