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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Digital Product Owner, Research Decision Intelligence - **Company:** Sanofi - **Location:** Morristown, NJ, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Confluence, JIRA, Bioinformatics, Collaborative Software, Computational Biology, Databases, Data Visualization, Data Warehousing, Web Browsers, Machine Learning, Scrum Methodology, Software Engineering, User-Centered Design, Website Wireframe, Cloud Platform System, Snowflake, Technical Debt, Information Technology, Data Lineage, Figma, Machine Learning Operations, Spotfire, Interactive Whiteboards, Data Pipelines - **Published:** June 11, 2026 - **Apply:** https://www.disabledperson.com/jobs/72964025-digital-product-owner-research-decision-intelligence ## About the Role * Hands-on experience with life science data browsing and visualization platforms such as Spotfire and D360. Familiarity with electronic lab notebooks (ELNs) including Benchling and Genedata Biologics is a plus. Ability to query databases directly, with Snowflake experience preferred. * 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 using diagrams including business process flows, scientific workflows, and data flow diagrams to align cross-functional and cross-cultural stakeholders., * Bachelor's degree required in Life Sciences, Computational Biology, Bioinformatics, Computer Science, or a related field. Master's or PhD is a plus, * A minimum of 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. * Strong experience with data visualization tools is required. * 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 Technical Skills * Solid understanding of drug discovery workflows and the challenges of computational and experimental research * 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 Soft Skills & Mindset * 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 Preferred Qualifications * Background spanning both wet-lab biology and computational/data science * Familiarity with data visualization tools, AI/ML concepts and their applications in life sciences (model types, outputs, uncertainty quantification, validation) * Experience with platform migrations, technology transitions, or new capability onboarding is a plus * Familiarity with life science data browsing platforms such as Spotfire, D360, or equivalent tools is desirable but not a must. * 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, All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs, and additional benefits information can be found here. ## Description Product Ownership & Delivery * Own and prioritize the product vision, roadmap, and backlog for your product line, 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 * Lead agile ceremonies (sprint planning, backlog grooming, retrospectives) and drive iterative product delivery with cross-functional pods * 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, * 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 * Lead usability testing sessions, synthesize feedback, and rapidly iterate to improve user experience * Independently sketch wireframes and low-fidelity mockups to communicate product vision to design and engineering teams. Adoption & Change Management * 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 Stakeholder Collaboration and Communication * 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 * Facilitate co-creation workshops, ideation sessions, and requirements gathering with diverse stakeholder groups * Communicate product Progress, value delivered, and adoption metrics to stakeholders and leadership with clarity and confidence; manage competing expectations and negotiate trade-offs with transparency and sound judgment ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Boost Productivity with AI: Figma & Playwright MCP Workflows - Aris Markogiannakis](https://www.wearedevelopers.com/videos/1768-boost-productivity-with-ai-figma-playwright-mcp-workflows-aris-markogiannakis) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [Designing the Future of Human<>Agent Collaboration](https://www.wearedevelopers.com/videos/1447-designing-the-future-of-human-agent-collaboration) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers)