Director, Statistical Genetics

Overview

Working with Us

Challenging. Meaningful. Life-changing. Bristol Myers Squibb offers opportunities to grow through ambitious, impactful work in biopharma, including cell therapy and drug discovery across therapeutic areas.

Bristol Myers Squibb emphasizes balance and flexibility with a variety of benefits and programs. Read more at careers.bms.com/working-with-us.

Position

Director, Statistical Genetics

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 across genomic, structural and molecular informatics; systems biology; patient selection and translational biomarker research; knowledge science, epidemiology and machine learning across drug discovery and development. We partner with scientific and clinical experts inside and outside the company to empower data-driven decisions across a pipeline of next-generation medicines.

Location: Cambridge, MA

Responsibilities

• Drive design and implementation of computational strategy to infer causal mechanisms driving disease using human genetics and other data types (e.g., Mendelian randomization with proteomics, TWAS, colocalization).

• Lead the team to perform cross-biobank analyses to identify mechanisms underlying human genetic risk factors (e.g., LD score regression, eQTL mapping, scRNAseq).

• Lead and coordinate with stakeholders to facilitate the use of germline genetics for discovery in neuro, immunology, and cardiovascular disease.

• Evaluate and prioritize multi-modal, disease-specific datasets to enable deep understanding of causal human biology in priority disease areas.

• Coordinate with stakeholders to nominate, evaluate and advance novel drug targets.

• Communicate findings and recommend follow-up actions in multiple settings (1:1, seminars, project meetings, and external publications).

Basic Qualifications

• Bachelor's Degree with 15+ years of academic/industry experience

• Or Master's Degree with 12+ years of academic/industry experience

• Or PhD with 8+ years of academic/industry experience

• 6+ years leadership experience

Preferred Qualifications

• PhD in statistical genetics or related computational/quantitative discipline

• 8+ years of relevant postdoctoral research and/or industry experience

• Experience applying genetics to drug discovery

• Deep scientific expertise in statistical genetic methods (GWAS, exWAS, Mendelian Randomization, colocalization, polygenic risk scores)

• Advanced hands-on knowledge of at least one programming language (R or Python)

• Familiarity with functional genomics preferred

• Demonstrated ability to advance multi-disciplinary team projects

• Managerial and mentorship experience in an industry setting

Compensation and Benefits

Compensation: Cambridge Crossing: $239,890 – $290,687 (base); additional incentive cash and stock opportunities may be available. Final compensation based on experience. Benefits vary by location and role; details at careers site.

Benefits highlights include:

• Health Coverage (medical, pharmacy, dental, vision)

• Wellbeing programs (e.g., EAP, wellness accounts)

• Financial protection (401(k), disability, life and travel insurance, etc.)

Work-Life and Accessibility

On-site/Hybrid/Remote : Site-essential roles require 100% onsite; site-by-design roles may allow hybrid work with at least 50% onsite; field-based/remote-by-design roles require travel as part of the job function.

Disability support : Reasonable accommodations available; inquiries to See equal employment opportunity information at careers.bms.com/eeo-accessibility.

Data protection : We do not request payments or sensitive information during recruitment. For privacy details, visit careers.bms.com/fraud-protection and careers.bms.com/privacy.

Legal and contact : For questions about the posting or your application, contact

Equal Opportunity : Bristol Myers Squibb is an equal opportunity employer; qualifications will be evaluated without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic.

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