Coface is characterized by a predominantly collaborative culture, placing people, trust and quality professional relationships at the core of its operations. A close management approach encourages guidance, empowerment and skills development within a supportive environment. This culture is strongly complemented by a competitive dimension, focused on performance, results and customer orientation. It is also supported by a structured organizational foundation ensuring rigor and reliability, while a more moderate innovation component contributes to adaptability and continuous improvement. [+]

Reporting to the Strategy and Development Department, the Data Lab brings together Data Science, AI, and Software Engineering skills to design, develop, and deploy operational solutions that improve the company's processes, products, and services. The team has about thirty people spread across Paris, Toronto, and Casablanca.

The Data Lab aims to implement best development practices, mainly in Python but also in React and Java, and manages CI/CD pipelines to deploy applications and APIs on Docker/Kubernetes infrastructures, on Apache Airflow, and in the Cloud.

Knowledge sharing through presentations among team members, training, and dedicated technology watch are part of the Data Lab's operating mode.

The use cases for data science are varied and lead to concrete implementations in internal tools and customer applications, for example:

• Scoring the risk of business failure


• Extracting information from images and documents


• Building and using knowledge graphs


• Search engine specialized in company identification


• Financial modeling and simulations

The missions:

• You will join Coface's Data Lab team and most often work in pairs or in small teams on innovative projects


• You will fully design and develop solutions that may implement Machine Learning technologies, all the way to deployment on our container infrastructures or in the cloud, and monitoring in production


• You will contribute to technology watch

• Engineering degree or equivalent in Data Science: supervised and unsupervised learning, clustering, NLP...


• Two or more years of experience in a similar role


• Proficiency in Python, its ecosystem, and good practices for code review and continuous integration


• Use of Linux and Git


• Autonomy, curiosity, rigor


• English: projects in international contexts

Appreciated skills:

• Experience in developing Python applications with high-quality standards


• Implementation of CI/CD pipelines


• Experience deploying Docker/Kubernetes and applications in the cloud


• Practice of SQL and experience in NoSQL databases (document, graph)