Scientist II/Senior Scientist, DEL Chemistry

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.

• Design, develop, and validate DEL synthesis schemes with high structural diversity using robust chemistries that complement our machine learning platform
• Develop, validate, and implement innovative on-DNA chemistry strategies while providing technical expertise in synthetic methods
• Collaborate with our Medicinal Chemistry and Machine Learning teams to enhance DEL library portfolio, hit expansion strategies, and hit confirmation activities
• Interface with selections team in designing DEL selections to various protein classes
• Contribute to the analysis of DEL data and aid guidance of computational tool design and methodologies that strengthen DEL data analysis
• Support hit generation activities across therapeutic areas
• Perform the synthesis of DNA-Encoded libraries and hits (on-DNA) internally and oversee synthetic chemistry through external partners (off-DNA)
• Lead cross-functional teams in drug discovery campaigns, bringing together experimental and computational expertise
• Drive the implementation of machine learning approaches in DEL design, screening, and analysis

• PhD in, Medicinal Chemistry, Chemical Biology, Computational Chemistry or related discipline with 4+ years of relevant experience
• MS with 8+ years or BS with 10+ years of relevant experience will also be considered

• 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

• Demonstrated scientific impact through publications, patents, or successful drug discovery programs ideally leveraging DEL technology against diverse targets
• Proven contributions to hit generation, hit-to-lead or lead optimization campaigns

• Demonstrated leadership in driving scientific projects and mentoring junior scientists
• Successful track record of cross-functional collaboration with computational, biological, and chemical teams
• Experience working effectively with CROs and external partners
• History of professional engagement that advances both organizational goals and the broader scientific field

• Exceptional analytical thinking and creative problem-solving abilities
• Strong organizational skills with ability to manage multiple priorities in a fast-paced environment
• Outstanding communication skills to effectively translate complex scientific concepts across disciplines
• Ability to thrive at the intersection of experimental chemistry and computational approaches
• Enthusiasm for working in a data-driven, machine learning-focused drug discovery environment

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:

• 401(k) plan with employer matching for contributions
• 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)
• Quarterly budget for books and online courses for self-development
• Support to attend professional conferences that are meaningful to your career growth and role's responsibilities
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe with daily lunch and breakfast for employees who are either onsite or hybrid
• Access to free onsite fitness center for employees who are either onsite or hybrid
• Access to a free commuter bus and ferry network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

#LI-Onsite

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.