Responsibilities

Manage products for AI‑driven tools supporting regulatory and other R&D; workflows, including regulatory strategy and innovation, productivity, document workflows, decision support, and automation.
Develop and maintain product roadmaps aligned with business objectives and evolving AI capabilities.
Collaborate with business and technology teams to define product strategy, vision, and execution with a cross‑functional product team, translating human‑centered workflows into clear requirements, wireframes, and user stories.
Support prioritization across competing initiatives, balancing impact and feasibility.
Identify opportunities where generative AI can streamline document creation, review, and knowledge access.
Partner closely with regulatory teams to develop solutions fit‑for‑purpose and integrated into key workflows.
Engage partners across R&D; to understand and incorporate opportunities for synergy.
Collaborate with data scientists, ML engineers, platform teams, UX, and business partners in a matrixed environment.
Support alignment among technical and business teams.
Provide product updates and insights to leadership across Data Science and Digital Health.
Support end‑to‑end product lifecycle from concept to launch and iteration.
Define user stories, acceptance criteria, and success metrics.
Manage backlogs and coordinate sprints with technical and design teams.
Ensure products meet quality, usability, security, and compliance expectations.
Partner with engineering teams on model integration, data prep, and evaluation cycles.
Apply knowledge of generative AI, RAG, agentic systems, and prompt engineering to shape product capabilities.
Collaborate with data and platform teams to leverage AI‑ready datasets and vector retrieval pipelines.




Support change management and adoption of AI‑enabled tools through onboarding and feedback loops.

Requirements

Advanced degree (MS/PhD) or equivalent experience in Life Sciences, Data Science, Computer Science, AI, or related field
6–8+ years of product management or digital product development experience
2–3+ years collaborating with data science/ML or analytics-driven teams
Experience contributing to AI/ML or generative AI product development
Familiarity with generative AI concepts (RAG, knowledge graphs, agent systems, evaluation frameworks)
Ability to translate workflows and data dependencies into product requirements
Experience with agile methodologies, UX principles, and product analytics
Experience in regulatory, R&D; operations, or scientific workflow environments (preferred)
Experience with developing generative AI tools in life science (preferred)
Exposure to data platforms, cloud architectures, and integrating AI services (preferred)
Comfort working with complex datasets and metadata schemas (preferred)
Understands AI/ML fundamentals and collaborates effectively with technical teams (preferred)
Bridges business needs with technical capabilities (preferred)
Breaks down workflows into modular product features (preferred)
Balances delivery with long‑term product vision (preferred)
Identifies opportunities to improve workflows using AI (preferred)
Synthesizes user input, technical constraints, and enterprise priorities (preferred)
Strong communicator across technical and non‑technical audiences (preferred)
Influences within matrixed environments (preferred)
Presents product progress and insights effectively (preferred)
Uses data to inform decisions and measure product success (preferred)
Strong critical thinking and ability to derive insights from complex info (preferred)
Experience with experimentation or evaluation frameworks preferred

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📌 Associate Director, Product Management (Madrid)
🏢 Jobtailor
📍 Madrid