Own Product Strategy & Definition - Work backwards from customer needs (as opposed to working forward from a specific technology) and drive clear, compelling product vision and definition as articulated via PRFAQs, Product Requirement Docs (PRDs), Pricing and Naming artifacts.
Rapid Concept Prototyping and Validation - Drive rapid, tangible experimentation by building and showing demos early and often, both internally and externally, to validate core hypotheses against real-world behavior and avoid misalignment
Plan the Work; Work the Plan - Own the 12-18 month strategic roadmap and its delivery with Engineering, R&D, and Design, manage the backlog for continuous improvement, and coordinate all product launch activities and collateral with Marketing and Legal
Establish Product Market Fit (PMF) - Prove and validate Product Market Fit (PMF) by partnering closely with design partners and lighthouse customers, working closely with them during definition and validation phases like PRFAQ authoring and running private betas
GTM scaling - Partner with Sales and Marketing to create collateral and training, inform revenue goals, monitor KPIs (like win rates), and review customer tickets to identify product insights and address defects

Requirements

5+ years as a Technical Product Manager / technical product leader in a Life Sciences focused software business
Experience taking Cloud/SaaS products from concept and definition through engineering design, launch, and go-to-market.
Deep understanding of the life sciences value chain, especially biopharma R&D workflows such as target identification, biomarker discovery, hit finding, lead optimization, preclinical development, translational science, and clinical evidence generation.
Fluency in life sciences data types and constraints, including omics, imaging, assay data, real-world data, EHR/claims, literature, and knowledge graphs, plus data quality, provenance, and interoperability considerations.
Ability to translate scientific user needs from researchers, clinicians, translational teams, medical affairs, and data scientists into product requirements without oversimplifying the science.
Ability to work in ambiguous, fast-moving environments and convert unclear customer problems into scalable product solutions.
Hands-on product leadership for AI/ML platforms or applications, including model-backed APIs, copilots, agentic workflows, or decision-support products.
Fluency in the AI product stack: model selection, inference, fine-tuning, retrieval, evaluation, prompt / agent design, human-in-the-loop workflows, observability, safety, and cost-performance trade-offs.
Working knowledge of regulated and semi-regulated environments, including GxP, HIPAA, privacy, model governance, validation, auditability, and evidence requirements for scientific and healthcare use cases.
MBA
PhD in Computational Chemistry, Computational Biology or Biomedical Engineering

Benefits

Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions
Retirement savings with company matching
Paid parental leave
Inclusive family-building benefits
Fully remote, Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance
Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Product StrategyProduct Requirement Docs (PRDs)Cloud/SaaSAI/ML platformsmodel-backed APIsdata qualityinteroperabilitymodel selectionfine-tuninghuman-in-the-loop workflows

Soft Skills

leadershipcommunicationproblem-solvingadaptabilitycollaboration

Certifications

MBAPhD in Computational ChemistryPhD in Computational BiologyPhD in Biomedical Engineering