Senior) Director, Translational Medicine and Diagnostics
Listed on 2026-08-03
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Software Development
AI Engineer (Applied/Software), Data Science Manager
The Opportunity
The unprecedented convergence of multi-modal data, advanced disease modeling, and computational power is revolutionizing drug discovery. insitro is harnessing this moment to redefine how medicines are developed for complex diseases. Our AI/ML-enabled platforms integrate and scale data to rapidly discover novel biological insights, identify new targets and drugs, and redefine complex diseases. To enable this vision, we are seeking a Director (or Senior Director) of Translational Medicine and Diagnostics.
This role is an opportunity to directly improve patients' lives by leading translational medicine across our three therapeutic areas — neurology/neurodegeneration, metabolism/cardiovascular, and ophthalmology — and by making clinical trials more efficient and beneficial for patients and drug developers through AI/ML and innovative translational strategies.
Reporting directly to the Chief Medical Officer, you will lead the translational medicine function at insitro, supporting the development of multiple therapeutics — biologics, oligonucleotides, and small molecules — along with multimodal biomarkers and diagnostics. This position can be onsite (three days per week) or hybrid (~one week per month) in our South San Francisco office, with additional travel to relevant medical and translational science conferences and health authorities.
ResponsibilitiesTranslational Strategy & Leadership
Build the Function: Build and lead insitro's translational medicine function, from IND/CTA through clinical proof-of-concept, across biologics, oligonucleotides, and small molecules
Lead Key Assets: Serve as translational lead for advanced pre-clinical and initial clinical-stage assets
Own End-to-End Strategy: Be accountable for translational medicine strategy, GCP adherence, and regulatory-authority interactions, including biospecimen CRO selection and oversight
Biomarker Science & Patient Stratification
Design Stratification Strategies: Design innovative approaches to patient stratification using laboratory and digital biomarkers
Generate Proof-of-Mechanism Evidence: Generate proof-of-mechanism evidence that drives objective, data-driven, and timely go/no-go decisions
Regulatory Strategy, Partnership & Influence
Interpret Regulatory Requirements: Interpret regulatory translational medicine requirements and quantify the return on investment of translational strategies
Partner Across Functions: Collaborate closely with preclinical, clinical, regulatory, and computational teams
Shape the Field: Influence emerging AI/ML policy in translational science through original publications, presentations, and stakeholder engagement
Experience & Qualifications
Advanced Degree: Advanced degree in life sciences, technology, chemistry, or a related discipline, or equivalent practical experience
Proven Tenure: 10+ years of experience in translational science in biotech and/or pharma, including direct experience as a translational lead delivering therapeutics and diagnostic biomarkers from FIH through proof-of-concept to NDA/BLA submission
AI/ML Exposure: Experience applying AI/ML approaches to drug discovery and development
Technical Breadth: Deep understanding of diagnostic and device regulations, good clinical practice, clinical trial design and execution, clinical pharmacology, biostatistics, and the application of computation to drug development
Core Competencies
Cross-Functional Collaborator: Track record of communicating and collaborating effectively with diverse stakeholders across clinical, translational, computational, and life sciences functions
Motivating Leader: Strong interpersonal skills that inspire others to do their best work
Patient-Driven: Genuine passion for bringing better medicines to patients in need
Our target starting salary for successful US-based applicants for this role is $224,000 - $299,000. 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.
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