Computational Scientist Catalyst

Position Title: Computational Scientist Catalyst

Department: Scaled Data Science Models

Location: Toronto, ON

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.

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 center of our ambitions. 

As one of Canada's leading investors in life sciences, manufacturing and research and development, we focus on delivering new and better ways to address unmet medical needs. Our life-changing and lifesaving products are grounded in science that Canadians can trust. 

Sanofi has embarked on a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of data adoption with artificial intelligence (AI) and machine learning (ML) tools. We strive to use AI and ML across the organization to accelerate functions like R&D, medical, manufacturing, and commercial performance. Our objective is to complement our business partners with AI to provide life-improving and lifesaving drugs and vaccines to patients faster and more effectively. 

About the Program 

You'll join the Sanofi Data and AI Future Catalyst Program as a Computational Science Catalyst - a 2-year rotational program that will provide you with an unparalleled opportunity to contribute to different products and learn around several aspects of our business domains. This opportunity will allow for personal and professional growth, as no two experiences will be alike and you'll have the opportunity to carve your own path. 

As a member of Sanofi's Global AI Centre of Excellence in Toronto, you will be working on a team that is globally diverse, with members here in Toronto as well as across our global hubs in France, Spain, USA, India and beyond. You'll be engaged in a structured program that's focused on driving the growth of your technical knowledge and business acumen in computational science. 

You'll work with multi-faceted teams operating in cross-functional pods as part of our AI Factory approach - bringing together data management, AI, and product development skills to create an agile, fulfilling and meaningful work environment. As part of catalyst, you will have the opportunity to bring your skills into different products within Digital R&D and/or Real-World Data. 

About the Role 

As a Computational Science Catalyst, you will adopt and extend advancements in the field of machine learning and generative AI to analyze and interpret data from pre-clinical, clinical and real world datasets in the healthcare and pharmaceutical industry. You will inform and accelerate the clinical research process, optimize R&D strategies, and ultimately improve patient outcomes. 

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: 

• Prepare and curate data from sources such as EHRs, clinical trials, preclinical research, medical imaging, digital pathology, registries, or real-world datasets. 

• Build and evaluate ML/GenAImodels to predict outcomes, identify risk factors, simulate scenarios, or support decision-making across R&D and clinical development. 

• Develop end-to-end analytics workflows – from exploratory analysis to experiment design to delivering production-ready models with guidance from senior scientists and engineers. 

• Support software development for data processing, model training, and visualization by writing clean, well-structured, and well-tested code. 

• Create clear narratives through data storytelling, and visualizations to communicate insights to technical and non-technical stakeholders. 

• Collaborate across multidisciplinary teams (engineering, product, R&D) to translate business questions into computational approaches. 

• Stay current with new methods in machine learning, generative AI, and computational science; share learnings with the broader team. 

• Document and communicate results, and occasionally contribute to internal technical reports, internal/external presentations, or open-source examples and draft publications. 

About You

Eligibility Requirements: 

• Must be legally authorized to work for Sanofi in Canada.

• Graduate degree (Master’s or PhD) in a quantitative discipline (e.g., computer science, engineering, mathematics, physics, statistics, computational biology, bioinformatics, economics). 

• Strong programming experience in Python (preferred), R, or a similar scientific programming language. 

• Experience with machine learning and/or generative AI - coursework, research projects, or internships. 

• Familiarity with common data workflows: cleaning, preprocessing, exploratory analysis, and model evaluation. 

• Exposure to genomics, digital pathology, medical imaging and healthcare-related data (EHR, clinical, or real-world datasets) is a plus but not required. 

• Basic familiarity with databases (SQL or NoSQL). 

• Strong written and verbal communication skills, including the ability to explain insights clearly. 

• Demonstrated ability to work in teams and contribute to collaborative projects. 

• Curiosity, problem-solving mindset, and enthusiasm for applying AI to life sciences and global health. 

Preferred Qualifications: 

• Exposure to topics such as: supervised/unsupervised learning, deep learning, sequence models, GenAI/foundation models, graph ML, causal inference, optimization, or time-series forecasting. 

• Experience building small applications or tools (e.g., pythonic libraries, dashboards, Streamlit apps, simple APIs). 

• Familiarity with software development practices (version control, testing, agile teamwork). 

• Interest in scaling ML systems using cloud platforms or modern data/ML tooling. 

• Experience with data visualization tools or ML-Ops concepts is a bonus. 

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.