Senior Data Product Owner

Role Overview

• Own the data product vision supporting R&D activities, from ideation to adoption.
• Challenge business needs, arbitrate priorities, and ensure alignment with the scientific and data strategy.
• Be accountable for the value delivered, operational impact, and adoption of the solutions.
• Translate complex business needs into clear functional specifications, user stories, and acceptance criteria.
• Build, prioritize, and maintain structured, value-driven backlogs.
• Facilitate Agile rituals (Scrum) as Product Owner: sprint planning, refinements, reviews.
• Work closely with data, IT, engineering, and scientific teams.
• Design and evolve complex scientific data models covering: molecule screening, plant phenotyping, analytical chemistry, bioinformatics, bioproduction, field trials.
• Ensure data consistency, quality, traceability, and usability across all R&D workflows.
• Lead or contribute to the integration and evolution of ELN / LIMS.
• Contribute to the design and industrialization of RAG (Retrieval‑Augmented Generation) solutions applied to scientific data (documents, protocols, experimental results, metadata).
• Collaborate closely with AI teams to structure, qualify, and expose the data required for GenAI use cases.
• Leverage GenAI tools to improve efficiency (ideation, prioritization, documentation, delivery).
• Apply design thinking principles to build user-centered solutions.
• Interact effectively with stakeholders at all levels, from technicians to executive leadership.
• Facilitate business workshops and co-creation sessions.
• Actively contribute to spreading a data culture across Micropep.
• Coach and support business teams’ data stewards.

Requirements

• Senior profile, with several years of experience as a Data Product Owner / Product Owner on complex data products.
• Proven experience in data product management (vision, delivery, adoption).
• Strong mastery of scientific data modeling.
• Significant experience in an R&D environment—biotech, life sciences, or a complex industrial setting.
• Good understanding of the challenges of scaling GenAI use cases.
• Solid hands-on experience with Agile / Scrum practices.
• Proficiency in SQL.
• Proven experience with ELN / LIMS, ideally Benchling.
• Fluent professional English required (written and spoken).

Tech Stack

• SQL

Benefits

• A key, cross-functional role at the heart of R&D and the data strategy.
• High-impact data products for scientific outcomes.
• An innovative, agile, international, fast-growing environment.
• The opportunity to sustainably structure Micropep’s data & AI foundation.