Digital Product Owner – Research Decision Intelligence

Sanofi•Cambridge, MA

4d•$113,250 - $163,583•Hybrid

About The Position

We are looking for a passionate, driven Digital Product Owner to join the Data Visualization & Decision Support product line within the In-Silico Research team, taking ownership of a critical digital product that empowers scientists to make faster, more confident, data-driven decisions. If you thrive at the intersection of science and technology, equally at home in a user discovery conversation with a bench scientist and a technical refinement session with an ML engineer and take pride in shipping solutions that change how research gets done, this role is for you. As Product Owner, you will own end-to-end delivery of one or more data visualization and decision support products, working in agile cross-functional pods alongside data scientists, ML engineers, UX/UI designers, and front-end developers. You will define the product vision, manage the backlog, translate complex scientific and computational requirements into actionable user stories, and drive adoption of tools that become indispensable to researchers' daily workflows. You will partner with the Product Line Owner to ensure your products deliver coherent, high-value experiences across the portfolio. Your success will be measured not just by what you ship, but by the measurable impact on scientific productivity and the pace of drug discovery. Ready to push the limits of what’s possible? Join Sanofi in one of our corporate functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world. About Sanofi We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Requirements

Bachelor's degree required in Life Sciences, Computational Biology, Bioinformatics, Computer Science, or a related field.
5+ years of experience in product management, product ownership, or related roles within pharmaceutical R&D, biotech, or life sciences.
Proven track record delivering digital products in scientific or technical environments, ideally involving AI/ML components.
Experience with data browsing and visualization tools for life science applications e.g. Spotfire, D360, etc.
Experience working in agile cross-functional teams (Scrum, Kanban) and managing product backlogs.
Demonstrated ability to conduct user research and translate findings into actionable product requirements.
Solid understanding of drug discovery workflows and the challenges of computational and experimental research.
Familiarity with data visualization tools, AI/ML concepts and their applications in life sciences (model types, outputs, uncertainty quantification, validation).
Understanding of databases, data pipelines, data quality, and cloud-based platforms.
Experience with product management and collaboration tools such as JIRA, Confluence, Figma, or Miro.
Exceptional ability to listen to scientists and end users—and turn what you hear into products they want to use.
Strong scientific translation skills: you can hold a credible conversation with a computational biologist and a business leader in the same afternoon.
Structured problem-solver who can navigate ambiguity, manage competing priorities, and make decisive trade-offs.
Clear, confident communicator who can influence without authority and build alignment across functions.
Change management mindset: patient, strategic, and persistent in driving adoption in scientific organizations.
Collaborative spirit and genuine curiosity—you want to understand the science, not just manage the backlog.
Growth mindset and enthusiasm for the rapidly evolving AI/ML landscape in drug discovery.

Nice To Haves

Master's or PhD is a plus.
Experience with platform migrations, technology transitions, or new capability onboarding is a plus.
Background spanning both wet-lab biology and computational/data science.
Experience delivering AI/ML-powered tools that achieved measurable adoption in research workflows.
Portfolio demonstrating scientific interface, data visualization, or platform projects.
Knowledge of regulatory considerations for AI/ML tools in pharmaceutical R&D.
Understanding of API integration, data pipeline concepts, and how backend architecture impacts user experience.
Track record of facilitating design-thinking workshops and co-creation sessions with diverse stakeholder groups.
Experience in large pharma environments with complex organizational structures and governance processes.

Responsibilities

Own and prioritize the product vision, roadmap, and backlog for your product, ensuring clear alignment with scientific priorities and Digital R&D strategy
Write clear, well-scoped user stories, acceptance criteria, and success metrics grounded in real scientist workflows
Make sound, data-informed prioritization decisions, balancing new feature development, technical debt, and user feedback
Establish regular touchpoints with software development teams to validate technical requirements and ensure optimal solution architecture
Drive products through governance stage gates with clear go/no-go recommendations, business cases, and executive summaries
Able to interpret what a data entity means in a biological context not just technically, but scientifically by asking the right questions of domain experts.
Capable of tracing data lineage end-to-end: from point of entry in an ELN, through a data warehouse such as Snowflake, to its visualization and consumption in tools like Spotfire. This systems-level understanding is essential for writing precise, unambiguous requirements.
Experienced in leveraging artifacts such as business process flows, scientific workflows, and data flow diagrams to align cross-functional and cross-cultural stakeholders.
Conduct continuous user research with R&D scientists to deeply understand their workflows, bottlenecks, data needs, and interface requirements
Champion user-centered design principles throughout the product lifecycle, partnering with UX/UI designers to create intuitive, scientifically accurate interfaces
Independently sketch wireframes and low-fidelity mockups to communicate product vision to design and engineering teams.
Build and execute targeted user adoption strategies for platform launches and transitions
Monitor usage metrics and user satisfaction continuously, using data to guide product evolution
Identify and proactively address barriers to adoption across different business functions and user personas
Demonstrate product value through compelling scientific use cases and measurable outcomes
Build strong partnerships with R&D scientists, computational biologists, data scientists, and ML engineers to ensure products meet real scientific needs.
Collaborate with the Product Line Owner on portfolio strategy, prioritization, and resource allocation
Communicate product progress, business value and impact delivered, and adoption metrics to stakeholders and leadership with clarity and confidence; manage competing expectations and negotiate trade-offs with transparency and sound judgment