Product Manager, Claude Science
Own the strategy and execution of a major Claude Science product area, partnering with researchers, engineers, and scientists to ship AI capabilities for scientific workflows. The role requires strong product leadership, scientific or technical depth, and expertise in AI evaluation and enterprise readiness.
About the job
Responsibilities
- Own the vision, strategy, roadmap, and execution for a major area of Claude Science while contributing to overall product direction.
- Interview and collaborate with working scientists across academic labs, biotech, pharma, and research institutes; translate workflows and feedback into priorities, requirements, and success metrics.
- Partner with research to improve Claude’s scientific capabilities by defining target behaviors, shaping evaluations, identifying failure modes, and feeding findings into model development.
- Drive model and feature launches end to end, including readiness criteria, cross-functional coordination, early-access programs, and launch execution.
- Identify scientific domains, data sources, tools, and integrations to support next, using user evidence, usage data, and market analysis.
- Prototype concepts with Claude before committing engineering resources.
- Partner with safeguards, policy, security, and go-to-market teams to deploy scientific capabilities responsibly.
- Drive enterprise readiness, including security and compliance reviews, administration and deployment controls, and procurement requirements for pharma and biotech.
- Prioritize across scientific domains, customer segments, and workflows; define MVP scope and make clear product tradeoffs.
- Define and track success metrics such as adoption, retention, time-to-result, and trust in outputs.
- Maintain an up-to-date view of the AI-for-science ecosystem, including models, tools, benchmarks, and competitors.
Requirements
- Product management experience shipping technical products with engineering and design, or equivalent experience as a founder, engineer, or scientist driving product direction.
- Scientific or deeply technical background sufficient to reason with domain experts and diagnose model performance on scientific tasks.
- Strong understanding of AI and large language model concepts, including model behavior, prompting, and evaluation methodology.
- Daily experience using AI tools.
- Data-driven prioritization grounded in usage data, evaluation results, and user evidence.
- Strong user empathy and ability to synthesize ambiguous or conflicting expert feedback.
- Ability to execute amid ambiguity and develop clear, simple solutions across scientific domains.
- Clear written communication and ability to align research, engineering, and go-to-market stakeholders through influence.
- Thoughtful assessment of the risks and benefits of deploying frontier scientific capabilities.
- Bachelor’s degree or equivalent combination of education, training, and experience in a relevant field.
Nice-to-haves
- 8+ years of product management or equivalent product leadership experience, including 0-to-1 development and scaling; founder experience is a plus.
- Advanced degree or hands-on research experience in biology, chemistry, physics, materials science, or a related field.
- Experience building software for scientists, such as computational biology, cheminformatics, lab informatics, simulation, or scientific data platforms.
- Experience building model capability evaluations or benchmarks, particularly agentic or scientific evaluations.
- Experience shipping products in life sciences, pharma, or regulated research environments, including data governance and compliance.
- Track record of launching ambitious products with commercial success or broad distribution.
- Experience designing trusted-access or staged-rollout programs for sensitive capabilities.
- Creative, hands-on approach to solving difficult technical and product problems.
Compensation
- Annual salary: $305,000–$385,000 USD.
- Hybrid policy: Staff are expected to work from an office at least 25% of the time; some roles may require more office time.
Skills
AI, LLMs, Prompting, Model Evaluation, Product Roadmap, A/B Testing, Scientific Workflows, Data Analysis, Security Compliance, Data Governance, Enterprise Software, Computational Biology, Cheminformatics, Lab Informatics, Scientific Computing
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