Senior Principal Data Scientist, Agentic AI

Job title: Senior Principal Data Scientist, Agentic AI

• Location: Waltham, MA

About the job

As Agentic AI Senior Principal Scientist within our Vaccines R&D Data and Computational Sciences (DCS) organization, you’ll define and execute the Agentic AI strategy for computational design across Sanofi's entire vaccine development portfolio. Ready to get started?

Join the team protecting half a billion lives every year with next-gen science, mRNA innovation, and AI-driven breakthroughs. In Vaccines, you'll help advance prevention on a global scale - and shape the future of immunization. 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. You'll serve as a scientific leader and cross-functional collaborator responsible for implementing agentic AI workflows across four capability areas: bioinformatics, nucleic acid design, protein AI models, and viral strain surveillance supporting also the build of AI agents for Translational Data Science workflows. This role sits at the intersection of cutting-edge science, advanced technology, and strategic leadership.

Join the team protecting half a billion lives every year with next-gen science, mRNA innovation, and AI driven breakthroughs. In Vaccines, you’ll help advance prevention on a global scale - and shape the future of immunization.

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.

About You

Minimum Qualifications:

• Masters in Computational Biology, Bioinformatics, Structural Biology, Computer Science, or a closely related quantitative discipline with 5+ years of experience in drug development, molecular design, computational biology, or a related quantitative field within pharmaceutical, biotech, or technology environments

OR

• PhD in Computational Biology, Bioinformatics, Structural Biology, Computer Science, or a closely related quantitative discipline with 3+ years of experience in drug development, molecular design, computational biology, or a related quantitative field within pharmaceutical, biotech, or technology environments.
• 3+ years of demonstrated track record of scientific contribution or R&D work

Preferred Qualifications:

Technical Skills

• Deep expertise spanning at least two domains: bioinformatics and genomics, nucleic acid sequence design, or protein structure prediction and design
• Experience developing, productionizing, and deploying AI and machine learning models applied to molecular property prediction
• Demonstrated experience with autonomous AI systems, large language models, or AI agents applied to scientific research or drug discovery workflows
• Fluency in scientific computing (Python, R) and familiarity with cloud-based computational infrastructure (AWS, Azure, or GCP)
• Fluent in English; French is a plus
• Postdoctoral training

Soft Skills

• Strong strategic thinking and business acumen, with ability to translate scientific vision into executable roadmaps and communicate priorities to stakeholders
• Exceptional cross-functional collaboration skills with experience at the interface of R&D, digital, and CMC functions
• Outstanding communication, presentation, and scientific writing skills with ability to distill complex computational concepts for diverse audiences including non-technical executives

Main responsibilities:

• Define and execute Vaccines R&D agentic AI strategy — Implement and lead the adoption of agentic AI workflows across four capability areas: bioinformatics, nucleic acid design, protein AI models, and viral strain surveillance
• Leverage and contribute to Sanofi's enterprise AI infrastructure — Champion the development and deployment of AI and machine learning methods, including autonomous AI agents, multi-step reasoning systems, and large language model workflows to accelerate computational design processes
• Collaborate across functions — Drive cross-functional collaboration with R&D, Digital, CMC, and Clinical teams to ensure computational design outputs are actionable, integrated, and aligned with downstream development needs
• Define and adopt best practices for agentic AI — Establish and enforce best practices for code generation, software engineering, data governance, model validation, and reproducibility across all computational workflows
• Pioneer AI-assisted workflows — explore autonomous workflows for scientific computing, data analysis, and application development; build internal capabilities that can be industrialized and scaled across Research, CMC, Translational and Clinical contexts.

…