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’slives and delivering compelling growth. Our deep understanding of the immune system –and innovative pipeline – enables us to invent medicines and vaccines that treat and protectmillions of people around the world. Together, we chase the miracles of science to improvepeople’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, vector databases, and cloud-native AI services
Experience building and deploying AI solutions on public cloud platforms such as AWS, or GCP and leveraging native AI/ML 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 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:
Experience in communicating with business, expressing important AI, GenAI & Agentic AI concepts in a non-technical way, interpreting feedback from business
Experience in leading the data science & AI projects and working closely with junior data scientists and data analystsAbility to proactively identify and manage blockers, risks, and interdependencies across agile teams
Strong problem-solving, decision-making, and prioritization skills in a fast-paced and evolving environment
Excellent written and verbal communication, business analysis, data visualization and data storytelling skills
Nice to have experience in life sciences and healthcare and experience in a complex global organization
A demonstrated ability to work and collaborate in a team environment, working with multi-cultural global team
Ability to work in a fast-paced, constantly evolving environment and to manage multiple prioritiesFluent in English (Other languages a plus)
When joining our team, you will experience:
An international work environment, in which you can develop your talent and realize ideas and innovations within a competent team
An attractive, market-oriented salary and other benefits
Flexible home office policy, with a possibility to work up to 40% of time from home / where you can easily schedule your office days
Collective life and accident insurance
Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact
Exposure to training and certification pathways for technical and functional skills from AWS, SnowFlake, Informatica and others
An individual and well-structured introduction and training of new employees and we will dedicate a Buddy for you to better navigate in your first weeks
Your professional and personal development will be supported purposefully
Why Choose Us?
Bring the miracles of science to life alongside a supportive, future-focused team.
Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs
This position is for a new vacant role that is now open for applications.
"Artificial Intelligence” refers to any systems that use automated processes, including algorithms and machine learning, to analyze data and make predictions, inferences, decisions, or recommendations without direct human involvement. These systems may process personal information to identify patterns, improve services, or support decision-making. The Company may use Artificial Intelligence for purposes including, but not limited to, resume screening and hiring, scheduling interviews or meetings, conducting surveys, matching skills with potential job openings, interview scoring, ensuring compliance with regulations applicable to our industry, and activities related to performance evaluation. Information collected and processed by the Company’s Artificial Intelligence systems may include the personal information detailed above and calendar availability. It excludes the information collected and processed for monitoring purposes. You should contact Human Resources if you have a question or concern regarding your personal information. You can also contact Canada’s Privacy Officer via Sanofi’s data subject request portal, Data Subject Rights Webform. The Data Subject Rights Webform can also be used to request access or correction of your personal information and file a complaint.
Sanofi is an equal opportunity employer committed to diversity and inclusion. Our goal is to attract, develop and retain highly talented employees from diverse backgrounds, allowing us to benefit from a wide variety of experiences and perspectives. We welcome and encourage applications from all qualified applicants. Accommodations for persons with disabilities required during the recruitment process are available upon request.
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All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs, and additional benefits information can be found here.
Toute compensation sera déterminée en fonction de l'expérience démontrée. Les employés peuvent être admissibles à participer aux programmes d'avantages sociaux de l'entreprise. Des informations supplémentaires sur les avantages sociaux peuvent être trouvées ici.
