Data Scientist / ML Engineer

With a presence in around 100 countries, Coface is a leading global player in credit insurance and risk management. Coface is also a recognized expert in business information, surety bonds, political risk, debt collection, and factoring. We help our clients secure their business activities to build more successful companies.

Directly sponsored by several members of the Group Executive Committee, the Data Lab brings together expertise in Data Science and Software Engineering to design, develop, and deploy operational solutions that improve the company's risk management, business processes, products and services. The steadily growing team now has around 30 members, mainly based in Paris, as well as in Toronto and Casablanca.

The team addresses many use cases for Data Science, involving a variety of Machine Learning and AI technologies. For example:

• Scoring the risk of business failure with Machine Learning models
• Extracting information from images and documents with Transformers and LLMs
• Identifying companies with a custom search engine using embeddings
• Building and mining knowledge graphs
• Financial modeling and simulations

The Data Lab's work includes solid Software Engineering practices to achieve operational integrations in internal tools and client applications. Data Lab’s developments also include data extractions from the company’s databases and management of CI/CD pipelines to deploy applications and APIs on Docker/Kubernetes infrastructures, Apache Airflow, and in the cloud.

Knowledge sharing through presentations between team members, training, and technology monitoring during dedicated time are all part of how the Data Lab operates.

Your missions:

• You join Data Lab team and most often work in pairs or small teams on innovative projects.
• You design and develop complete solutions, from data extraction and modeling to deployment on our container infrastructures or in the cloud, and monitoring in production
• You contribute to technology monitoring and knowledge sharing within the team