Director, Statistical Genetics

Responsibilities:
- Drive design and implementation of computational strategy to infer causal disease mechanisms using human genetics and other data types (e.g., Mendelian randomization with proteomics, TWAS, colocalization).
- Lead cross-biobank analyses to identify mechanisms underlying genetic risk factors (e.g., LD score regression, eQTL mapping, scRNAseq).
- Coordinate with research stakeholders to facilitate germline genetics discovery in neuro, immunology, and cardiovascular disease.
- Evaluate and prioritize multi-modal, disease-specific datasets for causal human biology.
- Coordinate to nominate, evaluate, and advance novel drug targets.
- Communicate findings and recommend follow-up actions (1:1s, seminars, project meetings, external publications).

Basic Qualifications:
- Bachelor’s + 15+ years academic/industry experience; or Master’s + 12+ years; or PhD + 8+ years.
- 6+ years leadership experience.

Preferred Qualifications:
- PhD in statistical genetics or related computational/quantitative field (with 8+ years postdoc and/or industry experience).
- Experience applying genetics to drug discovery.
- Expertise with statistical genetics methods (GWAS, exWAS, Mendelian randomization, colocalization, polygenic risk scores).
- Advanced R or Python.
- Familiarity with functional genomics.
- Ability to advance multi-disciplinary projects.
- Managerial and mentorship experience.

Benefits (explicitly listed): Health coverage (medical, pharmacy, dental, vision); wellbeing support; 401(k), disability, life and accident insurance, supplemental health, business travel protection, personal liability, identity theft benefit, legal support, survivor support.

Application instruction: If intrigued but not a perfect fit, apply anyway.