Global Head of RnD Data and Computational Science

Job Title: Global Head of RnD Data and Computational Science

Location: Cambridge, MA Morristown, NJ

About the Job

At Sanofi, we’re committed to providing the next-gen healthcare that patients and customers need. It’s about harnessing data insights and leveraging AI responsibly to search deeper and solve sooner than ever before. 

The Global Head of Data and Computational Science will lead Sanofi's enterprise-wide data science and computational capabilities, driving innovation at the intersection of digital technology and R&D. This strategic role sits within the Digital organization while orchestrating cross-functional collaboration between enterprise Data & AI teams, R&D business functions, and software engineering teams to accelerate scientific breakthroughs and optimize R&D outcomes.

Key success measures for the role include :

• Accelerate drug discovery and development timelines through computational approaches

• Optimize R&D investment decisions through data-driven insights

• Foster a culture of digital innovation across scientific disciplines

• Establish Sanofi as an industry leader in computational R&D approaches

• Drive measurable improvements in R&D productivity and success rates

Working as a core member of the Digital R&D Leadership Team, a member of the Digital Extended Leadership Team, and a frequent collaborator with the Digital Data & AI Leadership Team, this role ensures seamless integration between computational science capabilities and enterprise data and AI standards.

We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?

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Main Responsibilities

Relentlessly focus on business objectives and customer needs, while aligned with the overall global Sanofi digital strategy:

• Enable scientific breakthroughs and business transformation through best-in-class computational methods, novel in-silico workflows, and operational excellence that empower R&D teams to optimize experimental designs, focus capital allocation, and accelerate the pathway of new molecules to patient impact.

• Translate R&D digital strategies and scientific objectives into a coherent and value-based computational science strategy with clear roadmaps across data science, AI technologies, and in-silico workflows enabling scientific discovery, patient-centric drug development, and R&D decision making.

• Lead a diverse, global community of computational scientists, data scientists, and AI experts, both direct and matrixed, to high degrees of team engagement and scientific excellence. Be accountable for performance management, talent development, and capability building to keep pace with rapidly evolving computational technologies and scientific advancements.

• Engage externally as a thought leader and representative for Sanofi's computational science and AI-driven R&D initiatives, fostering collaborations and enhancing Sanofi's reputation in the field.  Manage R&D data and computational science publications and patents adherent to applicable policies and communications guidance.

• Directly manage R&D's Guiding Coalition for Computational Science and AI Innovation as the main decision body for R&D AI methods, validation, and scaling approaches. Apply strategic aims set by Digital R&D governance to prioritize investments. Monitor progress to sustain value delivery and scientific impact. Manage "pivots" as needed as computational technologies evolve and new scientific opportunities emerge.

• Operationally plan delivery through in-house expertise, academic partnerships, and industry collaborations, fostering Agile ways of working across multidisciplinary teams.  Be accountable for maintaining accurate and up-to-date information on plans, progress, and returns on investment.

• In collaboration with legal, quality, and compliance teams, monitor the global regulatory and scientific landscape to anticipate changes affecting computational approaches in R&D and responsib