Principal Scientist, Statistical Genetics

Company : Bristol Myers Squibb
Location : Cambridge, MA, 02141
Posted Date : 3 October 2025
Job Type : Other
Category : Scientific Research & Development
Occupation : Scientist
Job Details
Statistical Geneticist
Working with Us Challenging. Meaningful. Life-changing. Those aren't words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.
Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives.
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 design, implement, and oversee discovery and translational efforts for neuropsychiatric diseases using large-scale human genetic data. This role will sit within Informatics & Predictive Sciences, a globally distributed group driving innovative computational research for discovery and early development within BMS research.
A key focus will be aligning with company strategy for neuropsychiatric diseases to impact drug discovery using insights from causal human biology. This will include leading efforts to apply innovative statistical genetics methods to build and inform therapeutic hypotheses, identify indications and patient populations for programs, and analysis of clinical trial data for reverse translation. It will also include synthesizing and communicating key findings at cross-functional meetings.
This position offers an exciting opportunity to impact human health through innovative human genomics research. It is also an opportunity to work closely with the broader scientific community through pre-competitive collaborations (e.g. FinnGen, UK Biobank, UK Genes & Health, 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:
- Coordinate cross-biobank analyses focused on identifying human genetic risk factors for neuropsychiatric 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, colocalization, integration with scRNAseq)
- Evaluate and prioritize multi-modal, disease-specific datasets that will enable deep understanding of causal human biology of neuropsychiatric disease
- 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 8+ years of academic / industry experience
- Or Master's Degree 6+ years of academic / industry experience
- Or PhD 4+ years of academic / industry experience
Preferred Qualifications:
- PhD in statistical genetics, neurogenetics, or a related computational/quantitative discipline field with 4+ or more years of relevant postdoctoral research and/or industry experience preferred
- Experience in leading efforts to apply genetics to drug discovery
- Deep scientific expertise in application of statistical genetic methods (GWAS, exWAS, Mendelian Randomization, colocalization, polygenic risk scores)
- 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
If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
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