Lead Data Scientist
Toronto, Ontario, C6A, Canada
Listed on 2026-09-05
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IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer
Reference Number: R2868512
Position title: Lead Data Scientist
Department: Commercial Data Science
Location: Toronto, ON (Flexible working - 40% home office / week)
About The JobReady to push the limits of what’s possible? Join Sanofi in one of our corporate functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world.
About The Sanofi DigitalWe are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people’s lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the centre of our ambitions.
Sanofi’s Digital organization’s mission is to transform Sanofi into a data-first and AI first organization by empowering everyone with good data. Through custom developed AI products built on world class data foundations and platforms, the team builds value and a unique competitive advantage that scales across our markets, R&D and manufacturing sites. The team is located in major hubs in Paris, Lyon, Barcelona, Cambridge, Bridgewater, Toronto, Budapest and Hyderabad.
Join a dynamic, fast paced and talented team, with world class mentorship, using AI to chase the miracle of science.
We are seeking a highly skilled and visionary Lead data scientist to drive innovation and impact at the intersection of AI and Commercial Pharma operations. This role will be a part of the Digital Commercial Advanced Analytics and AI team, which operates under the Digital Global Business Units and is an integral part of Sanofi Digital Organization.
About SanofiWe’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.
Main Responsibilities- Lead the design, development, deployment, and scaling of enterprise AI, Machine Learning, Generative AI, and Agentic AI solutions that drive measurable business value across Commercial functions, some examples of use cases are
- Enhancing the patient journey through intelligent and personalized support
- Autonomous agents for omnichannel engagement
- AI & GenAI driven transformation of market access and payer strategies
- Conversational AI for data interactions and insights (Talk-to-data capabilities)
- Development of unified platform of sales, marketers and MSL users powered by multi-agent systems
- Agentic AI powered Market research and competitive intelligence platform
- Serve as the subject matter expert for complex AI initiatives, providing guidance on solution architecture, model selection, experimentation approaches, and implementation best practices
- Own the end-to-end lifecycle of AI products, from business problem framing and prototype development through deployment, operationalization, monitoring, and continuous improvement
- Partner closely with Product Owners, business stakeholders, Data Engineers, AI Engineers, and platform teams to translate business requirements into scalable AI solutions.
- Drive adoption of AI solutions by effectively communicating complex technical concepts, model outputs, and business insights to technical and non-technical audiences
- Contribute to the evolution of Commercial AI, data, and platform strategies through technical expertise, innovation, and industry best practices
- Ensure AI solutions comply with Responsible AI principles, governance requirements, security standards, and enterprise policies
- Develop and promote reusable frameworks, coding standards, accelerators, documentation, and best practices to improve delivery quality and efficiency
- Stay current with advancements in AI, Generative AI, and Agentic AI, evaluating emerging technologies and identifying opportunities to…
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