
Insitro is an operator of a data-driven drug discovery and development company that utilizes machine learning and high-throughput biology to transform the way that drugs are discovered and delivered…

Insitro is an operator of a data-driven drug discovery and development company that utilizes machine learning and high-throughput biology to transform the way that drugs are discovered and delivered…
Founded: 2018
Founder & CEO: Daphne Koller, Ph.D.
Headquarters: South San Francisco, California
Core approach: Machine learning + high-throughput biology for drug discovery
Notable financing: $400M Series C (Mar 2021) led by CPP Investments
Reported total capital: $643M (reported) / company statements ~ $800M including partnerships
Drug discovery and development using machine learning and high-throughput biology
2018
Biotechnology / Drug discovery
$400,000,000
The Opportunity
insitro uses advanced machine learning to analyze extensive biological and clinical data, aiming to improve the success rate of drug discovery and development. One of insitro's key platforms for generating small molecule therapeutics in neurological and metabolic diseases integrates DNA-encoded libraries (DEL) with machine learning. We are seeking a creative and data-oriented DEL synthetic chemist to lead lab-based DEL synthesis (on- and off- DNA) and data analysis. This role will play a key part in the application of machine learning to enhance the effectiveness and speed of our preclinical drug development programs. This position's reporting structure will be dependent on your specific skillset and will require you to be in our South San Francisco headquarters five days per week. Responsibilities
About You Education and Experience
Technical Expertise
Scientific Accomplishments
Leadership and Collaboration
Core Competencies
Compensation & Benefits At Insitro Our target starting salary for successful US-based applicants for this role is $135,000 - $180,000. 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:
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.
About Insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. 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. For more information on insitro, please visit www.insitro.com.
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Exposure to, knowledge of, and preferably hands-on experience, across aspects of DNA-encoded Library technology, including:
Library design and synthesis strategy
DEL selection methodologies and optimization
Next Generation Sequencing (NGS) data handling
Advanced DEL data analysis and interpretation
Hit confirmation and validation strategies
Proficiency with modern cheminformatics platforms, computational chemistry tools, and structure-based design approaches
Experience in data visualization, statistical analysis, and interpretation of large chemical datasets
Interest in integrating machine learning concepts with traditional DEL methodologies