Principal Scientist, Statistical Genetics

Bristol-Myers Squibb Company

Cambridge (MA)

On-site

USD 167,000 - 202,000

Full time

3 days ago
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Job summary

Bristol Myers Squibb in Cambridge, MA, is seeking a Principal Scientist, Statistical Genetics to lead and coordinate genetics analyses for cardiovascular diseases, using large-scale human genetic data within Informatics & Predictive Sciences.

You will apply methods such as GWAS, Mendelian randomization, colocalization, and rare variant analyses to identify drug targets, validate biology, and inform therapeutic hypotheses, with cross-functional collaboration and publication opportunities.

Qualifications

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

Responsibilities

  • Design and perform cross-biobank analyses focused on identifying human genetic risk factors for cardiovascular diseases.
  • Design and perform integrative analyses to infer causal mechanisms driving disease using human genetics and other data types.
  • 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).

Skills

Statistical genetics
Programming (R/Python)
Cardiovascular genetics
Cross-disciplinary collaboration
Data analysis

Education

Bachelor’s degree
Master’s degree
PhD

Job description

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 globally 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:
  • Subject to the terms and conditions of the applicable plans then in effect, you may be eligible to participate in our comprehensive benefit plans – including wellbeing support, retirement and financial protection benefits, and insurance offerings (medical, dental, vision, life and disability).
  • U.S.-based exempt employees are eligible for Flexible Time Off (FTO), which provides paid time off without a set accrual limit, subject to manager approval, along with 11 paid company holidays each year.
  • Non-exempt employees, RayzeBio employees, and employees located in Puerto Rico receive 160 hours of paid vacation annually for new hires (subject to manager approval), 11 paid company holidays, and 3 optional holidays.
  • Depending on eligibility, employees may also have access to additional time-off benefits, including paid sick leave, up to two paid volunteer days per year, summer hours flexibility, and leaves of absence for medical, personal, parental, caregiver, bereavement, or military needs. Eligible employees also enjoy an annual Global Shutdown between Christmas Day and New Year's Day.
  • U.S.-based job seekers can explore full benefit offerings at https://careers.bms.com/benefits
How We Work

Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.

Supporting People with Disabilities

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com . Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

For roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/

For roles based in Washington State only: If you live in or expect to work from Washington State if hired for this position, please visit this page for important information about the Washington Fair Chance Act.

Data Protection

We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection .

Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.com with the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.

R1607892 : Principal Scientist, Statistical Genetics

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