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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Digital Product Owner, Target Discovery - **Company:** Sanofi - **Location:** Cambridge, MA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Bioinformatics, Computational Biology, Databases, Data Architecture, Machine Learning, Scrum Methodology, Computer Networking Systems, Deep Learning, Data Pipelines, GXP, Unsupervised Learning - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=25d6d59cde201287 ## About the Role Bachelors Degree required, minimum 3-5 years of experience in life sciences product/project management, computational biology, bioinformatics, or related fields within pharmaceutical R&D or biotech, advanced degree in life sciences discipline strongly preferred * Required Skills: Technical Skills: * AI/ML Fundamentals - Understanding of machine learning concepts, model types (supervised/unsupervised learning, deep learning), and their applications in drug discovery * Target Discovery Domain Knowledge - Familiarity with target identification and validation processes, disease biology, biological pathways, and the drug development pipeline - hands-on experience with a variety of small, large, and macromolecule experimental methods ideal * Biological Data Literacy - Understanding of omics data (genomics, proteomics, transcriptomics), biological databases, and biomarkers * Bioinformatics & Computational Biology - Knowledge of common tools, platforms, and workflows used in computational target discovery * Data Architecture & Management - Understanding of data pipelines, data quality, integration of diverse biological datasets, and cloud platforms * Product/Project Management Methodologies - Proficiency in Agile/Scrum, roadmap planning, backlog management, and user story creation * Pharma Regulatory Landscape - Awareness of data privacy regulations (GDPR, HIPAA), validation requirements, and GxP considerations * Technical Communication - Ability to understand technical discussions with data scientists and translate requirements between technical and scientific teams Soft Skills: * Stakeholder Management - Building relationships with scientists, data scientists, IT, legal, and business leaders across the organization * Scientific Translation - Bridging the gap between computational scientists, wet-lab researchers, and business stakeholders * Strategic Thinking - Aligning product vision with therapeutic area strategies and business objectives * Prioritization & Decision-Making - Balancing competing priorities, managing trade-offs, and making data-driven decisions under uncertainty * Change Management - Driving adoption of AI tools in traditionally conservative scientific environments * Communication & Influence - Articulating complex technical concepts clearly and persuading without direct authority * Adaptability - Navigating the rapidly evolving AI landscape and shifting organizational priorities * Collaborative Leadership - Facilitating cross-functional teams and fostering a culture of innovation and experimentation, * Experience in or good understanding of Pharma R&D portfolio optimization in large pharma, or demonstrated ability to learn the business quickly * Strong networking, influencing and negotiating skills and superior problem-solving skills * Demonstrated experience leading design-thinking and ideation workshops with diverse groups of stakeholders * Experience in leading cross-functional teams and managing complex projects or programs * Excellent ability to listen to stakeholders and end users, ensuring products are built to address their specific needs and use cases Passion for leveraging AI and computational approaches to accelerate drug discovery and improve patient outcomes * ## Description Product Ownership & Development: * Own the product vision and backlog for specific target discovery AI/ML products * Create and maintain detailed product roadmaps aligned with scientific priorities * Write clear user stories and acceptance criteria for development teams * Manage sprint planning, backlog grooming, and product iterations in an Agile environment Prioritize features and requirements based on scientific impact and technical feasibility * Scientific Requirements & Delivery: * Gather and analyze requirements from scientific stakeholders * Translate complex biological needs into clear technical specifications * Work directly with development teams to ensure successful feature delivery * Validate that delivered solutions meet scientific user needs Drive continuous product improvement based on user feedback * Stakeholder Collaboration: * Build strong relationships with computational biologists and wet-lab scientists * Facilitate communication between scientific users and technical teams * Partner with data scientists to implement effective ML models * Work with IT teams to ensure robust data pipelines and infrastructure Engage with scientific stakeholders to understand evolving research needs * Product Adoption & Success: * Drive user adoption through training and documentation * Monitor product usage metrics and gather user feedback * Identify and address barriers to adoption * Demonstrate product value through scientific use cases Support users in integrating tools into their research workflows * ## Related Videos - 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