Job Title

Ready to push the limits of whats 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 peoples 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 lifesaving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions. As one of Canadas leading investors in life sciences, manufacturing and research and development, we focus on delivering new and better ways to address unmet medical needs. Our lifechanging 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 lifeimproving and lifesaving drugs and vaccines to patients faster and more effectively. Responsibilities Prepare and curate data from sources such as EHRs, clinical trials, preclinical research, medical imaging, digital pathology, registries, or realworld datasets. Build and evaluate ML/GenAI models to predict outcomes, identify risk factors, simulate scenarios, or support decisionmaking across R&D and clinical development. Develop endtoend analytics workflows from exploratory analysis to experiment design to delivering productionready models with guidance from senior scientists and engineers. Support software development for data processing, model training, and visualization by writing clean, wellstructured, and welltested code. Create clear narratives through data storytelling and visualizations to communicate insights to technical and nontechnical 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 opensource examples and draft publications. Qualifications Must be legally authorized to work for Sanofi in Canada. Graduate degree (Masters 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 healthcarerelated data (EHR, clinical, or realworld 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, problemsolving 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 timeseries 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 MLOps concepts is a bonus. Additional Information The unstructured data search team works on innovative AI/ML projects that accelerate our R&D pipeline, particularly in the preclinical and molecular design phases. Here are some examples in past projects: Designing an ML model for optimization and synthesis of lipid nanoparticles. Creating a generative AI model for insilico design of mRNA transcripts. Developing an active learning loop to integrate equivariant neural networks into protein structure prediction. Designing a closedloop system for automated synthesis optimization. For more information on these check out some of my previous posts! What we are looking for Graduate degree (Masters/PhD) in computer science or other quantitative discipline (e.g., engineering, mathematics, computational biology, computational chemistry). Strong mathematical and computer science fundamentals (linear algebra, probability, statistics). Ability to build architectures from the ground up. Fluent and proficient coder; minimal gap between translating an idea to a repository. Experience shipping software is a plus. Some chemistry and biology background is valued; double plus if completed multidisciplinary degree. Keywords Data Science AI Machine Learning Molecular Design #J-18808-Ljbffr