Senior Product Owner

PM

Senior Product Owner

PM
Centrum, Copenhagen

emagine Polska

Full-time
Any
Senior
Hybrid

Job description

The Product Owner will serve as the critical bridge between the line of business — medical experts, biostatisticians, and portfolio decision-makers — and a distributed, cross-functional product team spanning Copenhagen, London, India, and the USA.

This is a product leadership role, not a coordination function. The right candidate will hold a clear product vision, drive prioritization with confidence, manage complexity across time zones, and accelerate the adoption of a genuinely novel AI product into a regulated pharmaceutical environment.

Main Responsibilities

  • Owns the product vision and roadmap in close collaboration with the Design Lead, Tech Lead, and key business stakeholders, ensuring alignment from MVP through to scaled deployment and feature expansion.

  • Serves as the primary interface with the line of business — translating the needs of medical experts, biostatisticians, and clinical researchers into clear, well-scoped product requirements and user stories.

  • Manages and prioritizes the product backlog, balancing short-term delivery needs with long-term strategic value across a distributed team of frontend, backend, DevOps, and AI engineers.

  • Drives structured ways of working across a globally distributed team (Copenhagen, London, India, USA), ensuring clear handovers, asynchronous collaboration standards, and consistent delivery cadence.

  • Leads user onboarding and adoption, designing and executing change management initiatives that bring medical experts along on the journey from early adopter to embedded daily use.

  • Defines and tracks product success metrics — including time-to-insight, user activation and retention, innovation throughput, and ultimately the agent’s impact on Probability of Success (PoS) in clinical programs.

  • Facilitates continuous feedback loops between end users and the product team, ensuring the agent evolves based on real usage patterns and validated needs.

  • Collaborates with AI engineers and the Microsoft partnership team to translate complex AI capabilities — reasoning agents, code execution, SQL generation, and statistical analysis — into user-facing product value.

  • Ensures responsible AI deployment, working with governance, legal, and compliance stakeholders to maintain trust and regulatory alignment in a pharma R&D context.

Key Requirements

  • Proven track record as a Product Owner or Senior Product Manager on a digital or data/AI product, ideally with demonstrated ownership through a go-live and scaling phase.

  • Familiarity with the pharmaceutical or life sciences industry — understanding of clinical research, drug development processes, or R&D operations is essential.

  • Experience managing distributed, cross-functional teams across multiple time zones — structured, organized, and skilled at asynchronous communication and clear handovers.

  • Strong stakeholder management skills, with the ability to engage credibly with both highly technical AI/engineering teams and non-technical domain experts such as medical doctors and biostatisticians.

  • Hands-on experience with Agile delivery (Scrum, Kanban, or equivalent), including backlog management, sprint planning, and continuous delivery practices.

  • Fluency in English, written and verbal — the working language across all locations.

Nice to Have

  • Experience with AI, ML, or data-intensive products — ideally with exposure to LLMs, AI agents, or analytical tools.

  • Background in adoption and change management — particularly bringing domain experts (clinical, scientific, or operational) onto new digital tools.

  • Experience working in a product trio model (Product, Design, Engineering), with strong appreciation for collaborative, outcome-driven product development.

  • Familiarity with clinical data, biostatistics, or real-world evidence environments.

  • Prior experience in a scale-up or rapid growth product phase.

Tech stack

    English

    B1

    DevOps

    advanced

    Machine Learning (ML)

    advanced

    Change Management

    advanced

    Research & Development (R&D)

    advanced

    Governance

    advanced

    Artificial Intelligence (AI)

    advanced

    Stakeholder Management

    advanced

    Agile

    advanced

    SQL

    advanced

    Operations

    advanced

Office location