Associate Director, Product Management

Jobtailor; Madrid; Presencial; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

Jobtailor is seeking an experienced Product Manager to lead AI‑driven tools for regulatory and R&D workflows. You will shape product strategy, translate complex workflows into actionable requirements, and drive end‑to‑end lifecycle from concept to launch.

You will collaborate with data science, ML, and platform teams in a matrixed environment, maintaining roadmaps aligned to business objectives and evolving AI capabilities. Strong communication and agile practices are essential.

Formación

• 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

Responsabilidades

• 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.
• 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.

Conocimientos

Product management

AI/ML collaboration

Agile methodologies

UX principles

Data analytics

Effective communication

Cross-functional teamwork

Workflow translation

prompt engineering

Educación

MS/PhD in Life Sciences or CS or AI

Herramientas

Cloud architectures

Data platforms

Descripción del empleo

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