Digital Product Owner – Research Decision Intelligence

Main Responsibilities
- Own and prioritize product vision, roadmap, and backlog aligned with scientific priorities and Digital R&D strategy.
- Write user stories, acceptance criteria, and success metrics grounded in real scientist workflows.
- Prioritize features vs. technical debt using data-informed decisions and user feedback.
- Partner with software development teams to validate technical requirements and solution architecture.
- Drive delivery through governance stage gates with go/no-go recommendations, business cases, and executive summaries.

Scientific Data & Tools Proficiency
- Interpret biological data entities in a scientific context.
- Trace data lineage end-to-end (ELN entry → warehouse such as Snowflake → visualization/consumption like Spotfire).
- Use business process flows, scientific workflows, and data flow diagrams to align stakeholders.

User Research & Experience
- Conduct continuous user research with R&D scientists to understand workflows, bottlenecks, data needs, and interface requirements.
- Champion user-centered design; partner with UX/UI to build intuitive, scientifically accurate interfaces.
- Create wireframes and low-fidelity mockups to communicate product vision.

Adoption & Change Management
- Build and execute adoption strategies for launches/transitions.
- Monitor usage and satisfaction; use data to guide product evolution.
- Identify and address adoption barriers across personas/functions.
- Demonstrate value via scientific use cases and measurable outcomes.

Stakeholder Collaboration & Communication
- Partner with scientists and technical teams (computational biologists, data scientists, ML engineers).
- Collaborate on portfolio strategy, prioritization, and resourcing with the Product Line Owner.
- Communicate progress, impact, and adoption metrics; manage trade-offs transparently.

About You (Qualifications)
- Bachelor’s required in Life Sciences, Computational Biology, Bioinformatics, Computer Science, or related field; Master’s/PhD a plus.
- 5+ years in product management/product ownership in pharma R&D/biotech/life sciences.
- Track record delivering digital products in scientific/technical environments (ideally with AI/ML).
- Experience with life science visualization tools (e.g., Spotfire, D360).
- Agile cross-functional experience (Scrum/Kanban) managing backlogs.
- User research experience translating findings into requirements.
- Plus: platform migrations/technology transitions.

Skills
- Drug discovery workflow understanding; familiarity with data visualization and AI/ML concepts (model types, outputs, uncertainty quantification, validation).
- Knowledge of databases, data pipelines, data quality, and cloud platforms.
- Tools: JIRA, Confluence, Figma, or Miro.

Stand-Out (Preferred)
- Wet-lab + computational/data science background.
- Experience delivering AI/ML tools with measurable adoption.
- Portfolio of scientific interfaces/data visualization/platform projects.
- Knowledge of AI/ML regulatory considerations in pharma R&D; API integration and backend/user experience understanding.
- Workshop facilitation/co-creation; large pharma governance experience.