The Opportunity

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.

Responsibilities

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

About You

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

Compensation & Benefits at insitro

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.