Data Scientist Manager

Reference Number: R2868507 Position title: Data Scientist Manager Department: Commercial Data Science Location: Toronto, ON (Flexible working - 40% home office / week) About the job Ready 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 Digital: We 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 Data Scientist Manager to drive innovation and impact at the intersection of AI and Commercial 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 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. ​ Main Responsibilities: Lead and manage a team of Data Scientists and AI professionals, providing mentoring, coaching, performance management, career development, and technical leadership to build a high-performing organization Lead the design, development, deployment, and scaling of enterprise AI, Machine Learning, Generative AI, and Agentic AI solutions aligned with Sanofi's Digital Global Business Unit strategic priorities, 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 technical thought leader for product owners, business stakeholders, architects, engineers, and analytics teams by providing guidance on AI approaches, solution architectures, model selection, and implementation best practices Own the end-to-end AI product lifecycle from opportunity identification, business problem framing, experimentation, model development, deployment, operationalization, monitoring, and value realization across Commercial business functions Drive adoption of AI solutions by effectively communicating complex technical concepts and insights to executive and non-technical audiences through compelling storytelling and data-driven recommendations Establish and promote best practices, standards, reusable frameworks, and governance processes for AI, Machine Learning, Generative AI, and Agentic AI development across the organization Contribute to shape the Commercial AI, Data, and Platform strategies by contributing expertise on emerging technologies, operating models, and enterprise AI capabilities Ensure AI products adhere to Responsible AI principles, regulatory requirements, security standards, model governance frameworks, and enterprise risk controls Collaborate with global cross-functional teams across Product, Engineering, Data Engineering, Platforms, Architecture, and Business Functions to deliver scalable enterprise solutions Drive operational excellence by implementing MLOps and LLMOps best practices, establishing monitoring frameworks, managing model performance, and ensuring ongoing reliability of AI products Stay current with advances in AI, Generative AI, Agentic AI, machine learning, and industry trends, evaluating new technologies and identifying opportunities to accelerate innovation and business value Contribute to the broader Data Science and AI community through thought leadership, knowledge sharing, publications, innovation initiatives, patents, and technical communities of practice Support talent acquisition, workforce planning, and capability-building initiatives to strengthen the organization's AI and Data Science capabilities About you Required Qualifications: Master or PhD Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Physics, Computational Linguistic or a related field 6+ years of experience in Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics, or related disciplines, with a proven track record of delivering business impact through data-driven solutions 2+ years of hands-on experience in GenAI or LLM-based applications and familiarity of agentic AI frameworks 2+ years of experience leading, mentoring, or managing Data Scientists, ML Engineers, AI Engineers, or Analytics professionals in a matrixed or direct reporting environment Demonstrated experience owning and managing the end-to-end AI/ML product lifecycle, including problem framing, experimentation, model development, deployment, operationalization, monitoring, maintenance, and value measurement Strong expertise in machine learning methodologies including predictive modeling, classification, regression, forecasting, recommendation systems, optimization, causal inference, experimentation, and statistical analysis Hands-on experience designing and deploying enterprise Generative AI and LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt engineering, AI agents, multi-agent systems, and orchestration frameworks Deep understanding of model development best practices, MLOps, LLMOps, model evaluation, monitoring, observability, and production AI operations Strong programming skills in Python and experience developing production-grade, scalable, and maintainable software solutions using modern AI/ML frameworks and software engineering practices Experience working with structured and unstructured data, data engineering concepts, and modern data platforms such as Snowflake, vect