Senior Manager / Director, Statistical Genetics

insitro's mission is to bring better drugs faster to the patients who can benefit most, through machine learning and data at scale. Our strategy combines causal evidence from human genetics with in vitro cellular data from our automated wet-lab platforms to find causal genetic intervention points and carry them into therapeutic programs.

In this role you'll lead and grow an established team of statistical geneticists responsible for advancing our machine learning statistical genetics platform and using it to extract novel biological insight. You'll partner closely with ML scientists to develop novel phenotypes, with software engineers to build robust tools, and with computational biologists and therapeutic area scientists to turn genetic signals into programs. As the leader of this team, you'll set both strategic and technical direction, and structure the collaborations that move insitro's programs forward through a deeper understanding of causal human biology.

This position reports to the Senior Director, AI/ML (Human Genetics), and is remote-eligible within the US or based in South San Francisco with an in-person hybrid schedule of three days per week.

Team & Technical Leadership

• Lead the Team: Lead, mentor, and grow a team of four statistical geneticists developing methods to extract insight from human genetics

• Set the Direction: Define the roadmap and priorities for statistical genetics at insitro, and hold the bar for rigor

Methods & Platform Innovation

• Advance the Methods: Lead the team in building new ML methodology that extracts more signal from human genetics and integrates it with other data modalities

• Make It Reusable: Partner with software engineering to turn one-off analyses into well-tested workflows the whole research organization can run

Target Discovery & Translation

• Own the Analysis: Own GWAS, rare variant, and post-GWAS analyses across internal indications to identify and prioritize novel targets, moving from association to causal hypothesis

• Translate to Programs: Partner with therapeutic area and drug discovery scientists to convert genetic findings into validated, tractable programs

Experience & Qualifications

• Proven Tenure: PhD in statistical genetics, human genetics, computational biology, biostatistics, or a related field, plus 5+ years of experience

• Statistical Genetics Depth: Deep knowledge of statistical genetics as applied to target discovery in an industry setting

• People Leadership: Direct people management experience, with a track record of mentoring and growing technical talent

• ML Fluency: Demonstrated experience applying machine learning to genetic, imaging, or other clinical data

• Published Innovator: A history of publication and methodological innovation in statistical genetics

Core Competencies

• Cross-functional Communicator: You communicate clearly and collaborate easily across functions, including with experimental scientists and software engineers

Preferred Qualifications

• Engineering Fluency: Strong Python or R in a cloud environment, with a track record of reusable, tested, version-controlled code

• Disease Area Depth: Real understanding of a disease area relevant to insitro — cardiovascular, metabolic, liver, ophthalmologic, or neurological

• Discovery Track Record: Genetic discoveries that have shaped a real drug discovery decision or program

• Multi-modal Experience: Work with high-content modalities such as single-cell or bulk omics, genetic perturbation screening, spatial proteomics, or pooled optical screening

Our target starting salary for successful US-based applicants for this role is $224,000 - $273,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

• 401(k) plan with employer matching for contributions

• Excellent medical, dental, and vision coverage as well as mental health and well-being support

• Open, flexible vacation policy

• Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)

• Quarterly budget for books and online courses for self-development

• New hire stipend for home office setup

• Monthly cell phone & internet stipend

• Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid

• Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.

#LI-Hybrid

Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com, and if in doubt, contact us at [email protected]. 

About insitro

insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.