Principal Scientist, Computational Biology

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits.

This is work that transforms the lives of patients, and the careers of those who do it.

When you join BMS, you are joining a high-achieving team united by a common mission.

The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit.  IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS.

We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company.   We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers.

Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma.

We seek a creative and passionate computational biologist to join the Neuroscience, Immunology, and Cardiovascular (NIC) discovery team within Informatics and Predictive Sciences, a globally distributed group driving innovative computational research for discovery and early development. In this role, you will apply your analytical skills to single cell, multi-omics, spatial profiling as well as gene perturbation datasets generated from both patients and model organisms.

You will work as part of a cross-functional team focused on Neuroscience, Immunology and Cardiovascular early pipeline programs. In so doing, you will contribute to the discovery of targets and compounds that directly address unmet medical need in patients within NIC space.

Location: Cambridge, MA ; no fully remote option

Responsibilities

• Perform computational research and integrative analyses on multimodal biological profiling datasets (e.g. transcriptomic, proteomics, single cell omics, spatial profiling) that you help to design together with wet lab scientists 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 work as part of a cross-functional team to nominate and validate new targets for Neuro, Cardiovascular and Autoimmune diseases indications
• Work 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)
• Basic Qualifications
• PhD from a recognized institution in a quantitative field such as computational biology, computational genomics/genetics, computer science, statistics, mathematics, or other related discipline and 5+ years of post-graduate experience
• Advanced hands-on knowledge of at least one high-level programming language such as R or Python for computational research and reproducible research practices

Preferred Qualifications

• 5+ years of post-graduate experience in computational biology research (biopharma industry preferred) with track record (such as scientific publications) in driving and advancing research projects/programs with computational approaches
• 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 profiling (CITE-seq, scATAC-seq, perturb-seq) and/or spatial profiling to derive novel biological insights
• Strong quantitative skills, with hand on experience implementing and/or developing statistical methodologies and machine learning algorithms (such as single cell foundation models ) applied to the biological problems
• Background in human disease biology, especially in areas of autoimmune diseases strongly preferred
• Experience applying computer vision models to cellular imaging data preferred
• Experience utilizing  and applying AI agent such as claude coding to accelerate workflow preferred
• Scientific curiosity with an ability of self-learning
• Strong oral and written communication skills
• We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.