Grow

The Opportunity

At the heart of insitro’s strategy is the application of cutting-edge machine learning (ML) to biological data, both primary and clinical data as well as in vitro models, to discover and develop medicines that matter to patients. We are looking for a new team member who is an experienced computational scientist at analyzing diverse, multi-modal datasets to understand cancer biology, and is excited to embrace bold, new scientific approaches that leverage insitro’s ML platform to interrogate tumor biology in novel ways. We are a data-driven company, and believe that our best chance of achieving outsized impact comes from being unafraid to take non-traditional approaches in pursuit of delivering therapies to patients.

As an oncology-focused computational scientist at insitro, you will lead analyses of high-content, multi-modal human clinical data, alongside in-house multi-omic and imaging datasets, and perform data integration across the oncology therapeutic space. In addition to human clinical data, you will identify and leverage publicly available resources, together with diverse sources of prior knowledge for target and biomarker validation. You will also have the opportunity to collaborate closely with our experimental colleagues to design wet-lab experiments that will serve both to enhance our clinical data cohorts and to interrogate hypotheses derived from our analytical work. You will be part of a cross-functional team of life scientists, data scientists, engineers, and ML scientists working together to identify therapeutic targets and biomarkers with the goal of developing safe and effective drugs and delivering them to the right patients.

You will be joining a vibrant biotech startup that has long-term stability, due to significant funding, and is in a high-growth phase, and you will have many opportunities for significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!

About You

• PhD or MD/PhD in computational biology, systems biology, engineering, machine learning, or equivalent practical experience
• 8-12+ years experience in computational cancer biology, including both high content clinical and in vitro model systems
• A demonstrated track record of formulating high-impact questions in the cancer biology space and addressing them using cutting edge computational and machine learning tools
• Deep knowledge in one or more areas of cancer biology gained through firsthand research, and strong familiarity with other hallmarks of oncogenesis
• Extensive experience with scientific programming in Python and R, including expertise using numpy, scipy, bioconductor, and similar toolkits
• Experience with high-content data modalities, such as genomics (e.g., whole genome sequencing), transcriptomics (e.g., scRNA-seq), clinical imaging (e.g., digital histopathology), and/or spatial transcriptomics / proteomics
• Commitment to writing reusable code and documentation and familiarity with coding best practices (e.g., source control, testing)
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for making a difference

Nice to Have

• Experience deploying cutting edge machine learning methods (such as deep learning)
• Hands-on experience working with diverse functional genomic assays (RNA/DNase/ATAC/ChIP-seq, etc)
• Experience working with data from PDO/PDX models
• Publication record of meaningful contributions to high-quality work in relevant computational biology, systems biology, life sciences, or biomedical venues
• Experience working with clinicians or wet lab biologists to design experiments, both for data generation and to evaluate and follow up on computational findings
• Familiarity with cloud computing services (e.g., AWS or GCP)
• Demonstrated ability to write software in a team, industry experience or substantial involvement with open source projects
• Experience building infrastructure for data processing

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $200,000 - $225,000. 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
• Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees), as well as mental health and well-being support
• Open, flexible vacation policy
• Paid parental leave
• Quarterly budget for books and online courses for self-development
• Support to occasionally attend professional conferences that are meaningful to your career growth and development
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe with daily lunch and breakfast
• Access to free onsite fitness center
• Commuter benefits