Product Manager

Description We’re looking for a Product Manager to help turn complex science, customer needs, and AI capabilities into clear product direction. In this role, you will work closely with R&D, Science, Engineering, Data Science, Business Development, Product Marketing, and Customer-facing teams to define product requirements, prioritize needs, and support the development of AI-driven solutions for biomarker discovery, translational research, and clinical development in oncology. This is a great opportunity for someone with a strong scientific background, product orientation, and the ability to connect biology, data, technology, and real-world customer needs into meaningful product value. Responsibilities Translate product strategy and complex scientific, clinical, molecular, imaging, and AI-driven concepts into clear product requirements documents (PRDs), user stories, workflows, UX/UI requirements, acceptance criteria, and priorities. Gather and synthesize input from customers, pharma partners, scientific teams, and internal stakeholders to identify user needs, validate problems, and shape product direction. Own and support roadmap planning and prioritization based on customer needs, scientific value, business goals, technical feasibility, and product impact. Partner closely with Engineering, Data Science, R&D, UX/UI, and scientific teams to define feasible product solutions across data flows, model workflows, integrations, user experiences, and operational processes. Break down high-level product opportunities into development-ready features, user flows, edge cases, dependencies, MVP scope, phased release plans, and clear implementation priorities. Define end-to-end product workflows and screens that translate customer, scientific, and internal needs into usable, scalable, and development-ready product capabilities. Own product documentation, including feature definitions, acceptance criteria, workflows, release scope, and internal enablement materials. Work cross-functionally to define and deliver product capabilities, support product, scientific, and model-validation planning, and prepare launch and marketing materials. Define and track product success criteria using user feedback and product analytics, including user adoption, workflow efficiency, model and output quality, customer value, and post-launch product learnings. Requirements Advanced degree, MSc or PhD, in Life Sciences, Biomedical Sciences, Computational Biology, Immunology, Oncology, or a related field. 5+ years of experience in product management, product planning, scientific product strategy, data-driven product work, or a similar role in biotech, pharma, healthtech, AI, or computational biology. Strong understanding of biological, clinical, molecular, or imaging data, with the ability to translate scientific concepts into product needs. Experience working with multidisciplinary teams, including R&D, data science, biology, clinical, engineering, and commercial stakeholders. Strong understanding of software product development processes, including PRDs, user stories, acceptance criteria, backlog management, sprint planning, and release cycles. Technical fluency with software and AI product development, including data flows, integrations, APIs, model workflows, computational constraints, MVP scope, dependencies, and implementation trade-offs. Experience translating complex scientific, clinical, or AI-driven concepts into practical product requirements, screens, workflows, and development-ready specifications. Ability to create clear low-fidelity wireframes and collaborate with UX/UI teams to translate workflows, screen concepts, and user interactions into usable product experiences. Understanding of AI/model productization workflows, including data inputs, model outputs, validation, performance evaluation, human review processes, deployment considerations, and feedback loops. Experience working with AI tools to support product discovery, analysis, documentation, workflow design, and day-to-day product work. Strong analytical skills and ability to synthesize inputs from customers, business, science, and technology into clear product priorities. Excellent communication, presentation, and stakeholder-management skills. Comfortable working in a fast-moving startup environment with ambiguity, changing priorities, and high ownership. Strong organizational skills and experience writing clear product requirements, workflows, or technical/scientific documentation. Advantages: Experience with AI, machine learning, computational biology, digital pathology, multi-omics, or multimodal data platforms. Experience in oncology, biomarker discovery, translational research, clinical development, or pharma-facing products.