Lead Data Scientist

Reference Number : R2868512 Position title : Lead Data Scientist 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 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 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 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 create business value Mentor junior Data Scientists, AI Engineers, and interns through technical coaching, code reviews, solution reviews, and knowledge sharing Contribute to innovation initiatives, technical publications, patents, and AI 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 4+ 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, with 1+ years hands-on experience in GenAI or LLM-based applications and familiarity of Agentic AI frameworks Strong programming skills in Python or Java or other enterprise programming languages SQL/NoSQL query, familiarity with Spark, REST APIs, Golang, NodeJS, Angular, Typescript etc. Experience developing AI applications using modern frameworks and libraries such as LangChain, LangGraph & Transformers Strong expertise in machine learning methodologies including predictive modeling, classification, regression, forecasting, recommendation systems, optimization, causal inference, experimentation, and statistical analysis Strong understanding of agentic AI architectures, multi-agent systems, prompt engineering, tool/function calling, workflow orchestration, and AI application evaluation frameworks Knowledge of NLP tools like regex and fuzzy string matching Proficiency in working with variety of data assets (Structured and un-structured) hosted in different databases like Snowflake, vector databases, and cloud-native AI services Good understanding of agentic workflows, prompt engineering, and orchestration of multi-step AI steps by building AI agents Experience creating and deploying code libraries using functions, classes in Python in AI product-focused development under an agile environment Experience in production-ready model & software development Deep understanding on managing AI/Gen-AI end-to-end life-cycle management Experience working in cloud-based environment such as AWS or GCP or Azure and using cloud-technologies and native ML/GenAI tools for building AI-solutions Experience with various enterprise-level Application Programming Interfaces (APIs) Knowledge of regulatory, compliance and ethical considerations in AI/GenAI Nice to be already involved in an Agile/Scrum environment and Comfortable utilizing tools like Jira & Confluence Functional Skills: Proven ability to lead complex AI and Data Science initiatives involving multiple stake