.Job Requisition ID: R2767398Data Scientist R&D Lead- Hybrid- Full timeAbout the jobAt Sanofi, we're committed to providing the next-gen healthcare that patients and customers need. It's about harnessing data insights and leveraging AI responsibly to search deeper and solve sooner than ever before.The Global Innovation Centre is a crucial part of how we innovate, improving performance across every Sanofi department and providing a springboard for the amazing work we do. Build a career and you can be part of transforming our business while helping to change millions of lives. Ready?We are looking for a data scientist that can lead the application of machine learning models in the pharma R&D domain.The ideal data scientist joining our team will have experience applying machine learning algorithms to biomedical and clinical data. He/She will develop algorithms to enrich and complement the experimental results conducted by our R&D teams and will help build standard pipelines and tools to be used across the company by our research teams.The Data 4 New Technologies team is focused on developing methods to get value out of new life-sciences data sources. As such, the job will potentially work with diverse datasets like digital biomarkers, IoT medical devices, imaging data, amongst other biomedical datasets.We are looking for individuals ready to challenge the status quo to ensure development and impact of Sanofi's AI solutions for developing the drugs and improving the clinical trials that will benefit the patients of tomorrow. The ideal candidate will have a keen eye for improvement opportunities and a demonstrated ability to deliver AI/ML solutions while working across different technologies and in a cross-functional environment.Main responsibilities:Apply data science expertise in machine learning, deep learning, statistics, text-mining/NLP, forecasting and optimization to multiple biomedical analytics projectsBuild models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the-art machine learning technologiesDesign and implement algorithms to generate insights and visualizations derived from Digital Biomarkers experiments. Use open-sources and state-of-the-art scripts and libraries to complement and enrich biomedical datasets