Product Owner for AI & Molecular Modeling

Sanofi•Cambridge, MA

20h•$113,250 - $163,583•Hybrid

About The Position

At Sanofi, we chase the miracles of science to improve people's lives. We believe our cutting-edge science and manufacturing, fueled by data and digital technologies, have the potential to transform the practice of medicine, turning the impossible into possible for millions of people. The Digital In-Silico Research team is a key innovation engine within Digital R&D, dedicated to pioneering next-generation digital products that reshape how R&D discovers, designs, and develops new medicines. We harness cutting-edge AI, machine learning, and computational modeling to build transformative in-silico solutions—empowering scientists with predictive insights, streamlining complex workflows, and turning data into decisive action. As the Product Owner for AI & Molecular Modeling, you will play a pivotal role in bridging the gap between powerful computational predictive models and the medicinal chemists and computational chemists who rely on them. This position leads the vision and execution of AI/ML-driven digital products leveraging chemoinformatics, molecular modeling, and Computer-Aided Drug Design (CADD) methodologies, with a focus on small molecule drug design. This role sits at the intersection of cutting-edge AI/ML technology and user-centered design, where you will have a direct impact on how AI integrates into research workflows to drive scientific insights. You will partner closely with data scientists, ML engineers, and R&D scientists to translate complex technical capabilities into user-centered solutions that enable scientists to make faster, more informed decisions in molecular design, generation, and optimization. You will define product strategy, own product roadmaps and backlogs, and lead agile cross-functional teams to deliver iterative improvements that enhance user experience and accelerate adoption. A critical aspect of this role involves continuously evaluating research scientists' activities to identify bottlenecks and inefficiencies addressable through innovative digital solutions, and measuring the impact of delivered products at the executive level. Success in this role includes creating AI solutions that become essential tools in scientific research workflows, transforming how they leverage computational insights to drive scientific discovery and ultimately accelerating Sanofi's drug design pipeline. Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions.

Requirements

Bachelor's degree in Life Sciences, Computational Chemistry, Molecular Modeling, Cheminformatics, Biochemistry, Medicinal Chemistry or a related field.
5+ years of experience in product ownership and translating scientific business requirements into technical specifications.
Proven track record of leading cross-functional agile teams in a scientific or R&D environment.
Demonstrated experience delivering digital products with measurable scientific or operational impact.
Hands-on experience with AI/ML, molecular modeling, or CADD methodologies in a drug discovery context.
Experience defining and tracking product KPIs and communicating results to executive stakeholders.
Knowledge of CADD and molecular modeling methods: molecular docking, molecular dynamics, QSAR, free energy perturbation, pharmacophore modeling, and structure-based drug design.
Proven experience with AI/ML applications in drug discovery and small molecule design.
Strong command of agile product development methodologies (Scrum, Kanban) and cross-functional team leadership.
Ability to define, measure, and communicate product impact through KPIs and executive-level reporting.
Strong ability to translate complex computational concepts into intuitive user experiences.
Proficiency with product management tools (JIRA, Confluence, Figma, Miro, or equivalent).
Excellent communication and stakeholder management skills across scientific and business audiences.
Change management skills to drive adoption of new digital tools and workflows.

Nice To Haves

Master's or PhD degree
Hands-on experience with python-based libraries for molecular manipulation (RDKit, OpenBabel, DeepChem) and vizualization (Pymol, ChemPy, Streamlit, MDAnalysis).
Experience with generative AI or deep learning approaches for molecular design (e.g., graph neural networks, diffusion models, transformer-based molecular generation).
Track record of driving measurable improvements in user adoption, scientific productivity, or drug design cycle time.
Knowledge of regulatory considerations for AI/ML tools in drug discovery.
Experience with design thinking methodologies and facilitation of co-creation workshops.
Background combining wet-lab or medicinal chemistry experience with computational/data science expertise.
Curiosity and continuous learning mindset regarding emerging technologies in AI/ML and scientific computing.

Responsibilities

Lead agile and iterative product development in cross-functional pods with data scientists, ML engineers, UX/UI designers, and data engineers.
Define detailed user stories, acceptance criteria, and success metrics grounded in scientific workflows.
Coordinate with MLOps and data engineering teams to validate technical requirements and architecture decisions.
Ensure delivered products are scientifically rigorous, scalable, and accessible to non-computational scientists.
Drive continuous improvement cycles based on user feedback and adoption data.
Define, establish, and monitor KPIs and success metrics to demonstrate product value and return on investment.
Build and present executive-level reports and dashboards communicating product progress, adoption metrics, and value delivered.
Translate complex technical and scientific outcomes into clear business impact narratives for senior leadership.
Conduct regular product reviews with stakeholders to assess performance against strategic objectives.
Proactively identify and communicate risks, trade-offs, and mitigation strategies to leadership.
Coordinate and align cross-functional agile teams including data scientists, ML engineers, computational chemists, and UX designers.
Build partnerships with R&D scientists to deeply understand small molecule discovery workflows and pain points.
Collaborate with the Product Line Owner on portfolio strategy, prioritization, and resource allocation.
Facilitate co-creation workshops, sprint planning, and backlog refinement sessions.
Manage trade-offs between user needs, technical feasibility, and strategic priorities across stakeholders.
Conduct user research with molecular design scientists to understand workflows, data needs, and predictive modeling requirements.
Design intuitive interfaces and visualizations that make AI/ML predictions accessible, interpretable, and actionable.
Lead usability testing sessions and gather continuous feedback from scientist users.
Drive product adoption through targeted training, documentation, and change management initiatives.
Monitor adoption metrics and iterate on solutions to maximize engagement and scientific impact.
Serve as the primary translator between AI/ML and molecular modeling technical capabilities and scientific user needs.
Maintain deep knowledge of CADD methodologies (molecular docking, molecular dynamics, QSAR, free energy perturbation, pharmacophore modeling) to make informed product decisions.
Stay current on emerging AI/ML approaches in drug discovery, including generative molecular design, structure-based AI, and multi-parameter optimization.
Collaborate with data engineers to ensure robust data pipelines and APIs support seamless user experiences.
Ensure proper integration with existing molecular design tools, cheminformatics platforms, and scientific databases.