Insitro

Insitro

Senior Manager / Director, Statistical Genetics

South San Francisco, CA · Director

Sponsorship not specified$224k-$273kDetected 28 days ago
PythonCloud PlatformsMachine LearningBioinformaticsResearchLeadershipCommunicationMentoringBiostatistics

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odds of building a lasting career here

57Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role76
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level II · 2×
Level I$127,0261 entry
Level II$223,1422 entries
Level III$319,2383 entries
Level IV$415,3554 entries

Level III starts at $319,238 — $95,238 above the bottom of this range, and above its posted ceiling.

DOL prevailing wage, 2026-27 wage year · Chief Executives (11-1011) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

1 transfer filing in the last year, covering 1 worker. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • 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.
  • 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.

Responsibilities

  • Lead the Team: Lead, mentor, and grow a team of four statistical geneticists developing methods to extract insight from human genetics
  • 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
  • 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
  • Cross-functional Communicator: You communicate clearly and collaborate easily across functions, including with experimental scientists and software engineers
  • 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.

Nice to have

  • Strong Python or R in a cloud environment, with a track record of reusable, tested, version-controlled code
  • Real understanding of a disease area relevant to insitro - cardiovascular, metabolic, liver, ophthalmologic, or neurological
  • Genetic discoveries that have shaped a real drug discovery decision or program
  • 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
  • Experience & Qualifications

Skills

  • insitro's mission is to bring better drugs faster to the patients who can benefit most, through machine learning and data at scale.

Compensation

  • 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.
  • 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.

Benefits

  • 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)
  • New hire stipend for home office setup
  • Monthly cell phone & internet stipend
  • ML Fluency: Demonstrated experience applying machine learning to genetic, imaging, or other clinical data
  • 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.
  • 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

Company info

  • 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

Equal opportunity

  • insitro is an equal opportunity employer.
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This listing is sourced directly from Insitro's careers page and normalized into a canonical job model.