Scientist II, Arrayed Screening

About the role

The Opportunity The unprecedented convergence of multi-modal data and AI has the potential to revolutionize drug discovery. insitro is harnessing this moment to redefine how medicines are developed for complex diseases. Our success depends on our ability to attract, develop, inspire, and retain amazing, diverse talent and build a collaborative, high-performing, inclusive, and equitable culture. insitro is seeking a highly motivated Scientist II, Arrayed Screening to join our experimental biology and screening organization.

Responsibilities

• Develop, optimize, and execute arrayed screening assays in 96- and 384-well plate formats, including endpoint, kinetic, imaging-based, and/or biochemical readouts.
• Design and implement cell-based screening workflows using immortalized, primary, iPSC-derived, or engineered cellular models.
• Support small-molecule, genetic, and/or perturbational screening efforts, including assay development, target validation, mechanism-of-action studies, and screening campaigns.
• Partner with automation and process engineering teams to scale assays using liquid handlers and screening platforms such as Echo, Hamilton, Bravo, Tecan, or similar systems.
• Analyze screening and assay data using appropriate statistical and visualization tools; identify trends, troubleshoot assay performance, and communicate results clearly.
• Collaborate with ML and data science teams to ensure experiments generate reproducible, well-annotated, model-ready datasets.
• Translate biological questions into scalable experimental designs and work cross-functionally with disease biology, genetics, cell modeling, and drug discovery teams.
• Maintain rigorous documentation in Benchling/LIMS systems and contribute to best practices for assay robustness, reproducibility, and data quality.
• Present experimental plans, results, and recommendations to multidisciplinary project teams.

Requirements

• PhD in cell biology, molecular biology, biochemistry, pharmacology, bioengineering, chemical biology, or related fields.
• 2–5 years of relevant post-PhD or equivalent industry experience, with demonstrated independence in assay design and project leadership.
• Strong hands-on experience developing and running cell-based assays in high-throughput plate formats.
• Experience with high-content imaging, fluorescence/luminescence assays, viability assays, reporter assays, immunostaining, flow cytometry, or other quantitative cellular readouts.
• Strong mammalian cell culture skills, including aseptic technique and experience with immortalized, primary, stem-cell-derived, or engineered cell systems.
• Familiarity with molecular biology approaches such as cloning, CRISPR/gene editing, transgene expression, stable cell line generation, qPCR, or related methods.
• Experience with screening automation and liquid handling platforms is strongly preferred.
• Comfortable working with small molecules, biologics, siRNA/ASO, CRISPR reagents, or other perturbation modalities.
• Ability to analyze, interpret, and clearly communicate complex biological datasets.
• Experience with GraphPad Prism, Spotfire, Benchling, Python, or R.
• Comfortable working in a multidisciplinary environment that brings together biology, engineering, data science, and machine learning.

Qualifications

• Experience in biotech or pharma high-throughput screening.
• Experience developing phenotypic assays for disease-relevant human cell models.
• Experience generating datasets for machine learning, image analysis, or quantitative modeling.
• Familiarity with assay miniaturization, automation troubleshooting, Z-factor / assay quality metrics, dose-response analysis, or screening data QC.
• Experience working across therapeutic areas such as neuroscience, metabolic disease, oncology, immunology, or rare disease.

Skills

• Hands-on experience in cell-based assay development, high-throughput screening, mammalian cell culture, and quantitative data analysis.
• Strong communication and collaboration skills.
• Experience with ML and data science tools.
• Ability to analyze and interpret complex biological datasets.

Benefits

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 with a 401(k) plan with employer matching for contributions, excellent medical, dental, and vision coverage as well as mental health and well-being support, an open, flexible vacation policy, paid parental leave, a 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, a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area, and quarterly budget for books and online courses for self-development.

Pay

At Insitro, our target starting salary for successful US-based applicants for this role is $136,000 - $145,000. 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.

Schedule

This role requires you to be onsite at our South San Francisco office 5 days per week.

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.