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# Senior Principal Data Scientist, Agentic AI

- **Company:** Sanofi
- **Location:** Waltham, MA, United States
- **Experience:** Expert
- **Salary:** $148,500 - $214,500
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Bioinformatics, Cloud Computing, Code Generation, Computational Biology, Data Governance, Python (Programming Language), Machine Learning, Scientific Computating, Software Engineering, AI Infrastructure, Large Language Models, Model Validation, Agentic-AI, Information Technology
- **Published:** November 7, 2026
- **Apply:** https://sanofi.wd3.myworkdayjobs.com/en-US/SanofiCareers/details/Waltham-MA/Senior-Principal-Data-Scientist--Agentic-AI_R2873425-1

## About the Role

* 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, * 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, 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, Better is out there. Better medications, better outcomes, better science. But progress doesn't happen without people - people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let's be those people.

## Description

* 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.
 * Harmonize organization-wide agentic AI practices - build a community of agentic AI experts to implement best practices across the broader DCS organization; mentor scientists in adopting AI-assisted workflows for their R&D activities.