Insitro

VP, Bioassays, Cell Models, and Genomic Screening

South San Francisco, CA · Vp

Sponsorship not specified$12k-$15kDetected 298 days ago

Machine LearningData ScienceBioinformaticsAnimal StudiesLeadershipCommunicationCritical ThinkingMentoring

About the role

At insitro, we're revolutionizing drug development.
We fuse cutting-edge machine learning with large-scale biology and modality-independent drug discovery to tackle major bottlenecks in the pipeline.
We've built a leading platform and a team of incredibly talented scientists driven to make a real difference.

Direct, establish, and design bioassays and phenotypic screens to deeply investigate target/pathway biology using human disease-relevant cell-based models
You'll also support CRO monitoring and outsourced activities
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.
Design impactful assays: Direct, establish, and design bioassays and phenotypic screens to deeply investigate target/pathway biology using human disease-relevant cell-based models
Support to attend professional conferences that are meaningful to your career growth and role's responsibilities

Some travel for conferences, collaborations, and regulatory interactions may also be required.
A graduate degree in a technical field (biology, chemistry, biochemistry) or equivalent practical experience
12-15+ years of experience in the pharmaceutical/ biotech industry
Extensive experience with a wide spectrum of state-of-the-art cellular, biochemical, and imaging-based assays
Experience navigating complex genetic, small molecule, large molecule, and oligonucleotide cellular assays

Exceptional communication and influencing skills at all organizational levels, including executive leadership
Robust analytical capabilities, including strong quantitative and qualitative assessment skills, and demonstrated critical thinking

Our target starting salary for successful US-based applicants for this role is $290,000 - $326,000.
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

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.
Set the strategic vision for cell models, image based and genomic screens, as well as bioassay development and execution across all therapeutic areas, fueling our target and drug discovery ML engine
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

Lead and mentor a team of 20+ scientists, empowering them to achieve and exceed company goals
Cultivate talent: Lead and mentor a team of 20+ scientists, empowering them to achieve and exceed company goals

This listing is sourced directly from Insitro's careers page and normalized into a canonical job model.