Principal Scientist, Statistical Genetics

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.

Principal Scientist, Statistical Genetics

At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science. In oncology, hematology, neurology, immunology and cardiovascular disease – and one of the most diverse and promising pipelines in the industry – each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.

We seek a talented statistical geneticist to coordinate and lead implementation of genetics approaches to cardiovascular diseases using large-scale human genetic data. This role will sit within Informatics & Predictive Sciences, a globably distributed group driving innovative computational research for discovery and early development within BMS research.

A key focus will be applying genetics approaches to identify and validate drug target candidates with strong causal human biology that are aligned with company strategy for cardiovascular diseases. This will involve application of innovative statistical genetics methods that combine human genetic data with functional and clinical data (e.g., GWAS, fine-mapping, colocalization, Mendelian Randomization, rare variant associations tests, variant effect prediction, and polygenic modeling methods) to build and inform therapeutic hypotheses, including directionality, efficacy, safety, and indication selection. It will also include synthesizing and communicating key findings at cross-functional target discovery meetings.

This position offers an exciting opportunity to impact human health through innovative human genomics research, and will enable disease areas team in BMS research to leverage genetics for programs. It is also an opportunity to work closely with the broader scientific community through pre-competitive collaborations (e.g. FinnGen, UK Biobank, Alliance for Genomic Discovery), and to publish and present industry-leading work in this area.

Location: Cambridge, MA

Responsibilities will include, but are not limited to, the following:

• Design and perform cross-biobank analyses focused on identifying human genetic risk factors for cardiovascular diseases (e.g. GWAS meta-analysis, rare variant burden tests)
• Design and perform integrative analyses to infer causal mechanisms driving disease using human genetics and other data types (e.g. Mendelian randomization with proteomics, single-cell eQTLs)
• Leverage disease specific datasets that are multi-modal and derived from disease focused consortia
• Coordinate with stakeholders across research to nominate, evaluate, and advance novel drug targets
• Communicate findings and recommend follow up actions in multiple settings (including 1:1, seminars, project meetings, and external publications)

Basic Qualifications:

• Bachelor’s Degree with 8+ years of academic / industry exepereince
• Or Master’s Degree with 6+ years of academic / industry experience
• Or PhD with 4+ years of academic / industry experience

Preferred Qualifications:

• PhD in statistical genetics, cardiovascular genetics, or a related computational/quantitative discipline field with 4+ or more years of relevant postdoctoral research and/or industry experience preferred

• Experience applying genetics to drug discovery or other healthcare-related applications
• Deep scientific expertise in application of statistical genetic methods for causal inference
• Advanced hands-on knowledge of at least one high-level programming language such as R or Python
• Familiarity with functional genomics preferred
• Demonstrated ability to advance multi-disciplinary team projects required

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.

Compensation Overview:

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


The starting pay range(s) listed above is for full-time employees (FTE). You may also be eligible for additional discretionary incentive cash and stock opportunities. We determine starting pay thoughtfully – carefully considering the nature of the role, required skills, work location, schedule and the knowledge and experience you bring. Final compensation is guided by pay equity principles and applicable employment laws. Compensation programs are reviewed on an ongoing basis and may be adjusted over time to reflect evolving market factors, and individual, team or Company performance.

Benefits:

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