Data Scientist R&D Lead
Location: Barcelona - Spain
Hybrid Full time
About the job
At 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.
We are looking for a data scientist that can lead the application of machine learning models in the pharma R&D domain.
Main Responsibilities Apply data science expertise in machine learning, deep learning, statistics, text-mining/NLP, forecasting and optimization to multiple biomedical analytics projects.Build models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the-art machine learning technologies.Design 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.Work on the full spectrum of activities, from conducting ML experiments to delivering production-ready models.Use data analysis, visualization, storytelling, and data technologies to scope, define and deliver AI-based data products.Work closely with product owners, developers, engineers, and MLOps to deliver AI/ML solutions.Adhere to and promote best practices and standards for data science processes (including documentation) and code developments.Remain up to date with industry practices and emerging technologies such as generative AI and test creative ways of offering AI solutions to enhance existing solutions.Mentor and coach junior data scientists and interns.About You Experience developing methods for analyzing biomedical data.Hands-on AI/ML modeling experience with complex datasets combined with a strong understanding of theoretical foundations of AI/ML.Expertise within most of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, time series analysis, Bayesian statistics, signal processing.Experience creating and deploying code libraries using functions, classes in Python in AI product-focused development under an agile environment.Excellent written and verbal communication, business analysis, data visualization and data storytelling skills.A demonstrated ability to work and collaborate in an interdisciplinary team environment.Strong interest in the use of ML methods in the life and medical sciences to improve patient lives.Expertise with core data science languages (such as Python, R), and familiarity with different database systems (e.g., SQL, NoSQL).Comfortable working in cloud and high-performance computing environments (e.g., AWS, GCP, Databricks, Apache Spark).Experience in production-ready software development.
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