Alix Tiran-Cappello

In the world of data, inconsistencies or inaccuracies often presents a major challenge to extract valuable insights. Yet the number of robust tools and practices to address those issues remain limited.

Scaling machine learning at large organizations like Renault Group presents unique challenges, in terms of scales, legal requirements, and diversity of use cases. Data scientists require streamlined workflows and automated processes to efficiently deploy models into production.