Remote Head of Statistical Genetics & ML Platform

insitro.com; South San Francisco (CA); Hybrid; USD 224,000 - 273,000; Full time

Benefits offered by this job

401(k) plan with employer matching

Medical, dental, and vision coverage

Open, flexible vacation policy

Paid parental leave (≥16 weeks)

Home office stipend

Job summary

insitro is seeking a senior leader for statistical genetics to guide a team of four geneticists, defining the roadmap and setting technical direction for ML-driven genetics research. You will partner with software and therapeutic teams to turn insights into drug discovery programs.

The role requires a PhD with 5+ years in industry, deep genetics expertise, and a track record of mentoring technical talent, publishing work, and applying ML to biomedical data.

Qualifications

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

Responsibilities

• Lead, mentor, and grow a team of four statistical geneticists.
• Define the roadmap and priorities for statistical genetics at insitro, and uphold rigor.
• Lead the team in building new ML methodology that extracts more signal from human genetics.
• Partner with software engineering to turn analyses into reusable workflows for the organization.
• Own GWAS, rare variant, and post-GWAS analyses across internal indications to identify and prioritize novel targets.
• Translate genetic findings into validated, tractable programs with therapeutic area scientists.

Skills

People leadership

ML fluency

Cross-functional communication

Statistical genetics depth

Publication history

Education

PhD in statistical genetics or related field

Tools

Python

R

Job description

insitro is seeking a senior leader for statistical genetics to guide a team of four geneticists, defining the roadmap and setting technical direction for ML-driven genetics research. You will partner with software and therapeutic teams to turn insights into drug discovery programs.

The role requires a PhD with 5+ years in industry, deep genetics expertise, and a track record of mentoring technical talent, publishing work, and applying ML to biomedical data.