Data Scientist

Join our dynamic team as a Data Scientist in the Fraud Data Science team. You will play a crucial role in shaping future products and solutions, focusing on fraud detection using machine-learning-based solutions. Your work will span the full development lifecycle, from idea generation to deployment and ongoing support. You will also communicate insights and model outcomes to both technical and non-technical audiences.

• Contribuer à des initiatives à fort impact axées sur la détection de la fraude, en utilisant des solutions basées sur l'apprentissage automatique.
• Participer à l'ensemble du cycle de développement, de la génération d'idées et de l'expérimentation à la mise en production, à la surveillance et au support continu.
• Transformer de grands ensembles de données complexes en informations exploitables, recommandations et décisions basées sur les données.
• Familiarity with data warehouse concepts, ETL strategies and data engineering best practices
• MSc in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field (PhD preferred)
• Proficiency in SQL and Git, with hands‑on experience collaborating in shared codebases
• A strong track record of building robust, maintainable, high‑quality code
• Strong communication and collaboration skills, with the ability to work across disciplines
• Experience productionizing machine learning models, including monitoring, maintenance, and MLOps practices
• 2+ years of experience programming in Python, with a solid understanding of software engineering best practices (modularity, code reusability, version control, repositories)
• Ability to operate optimally in a data‑driven software engineering environment and translate data into business value
• 2+ years of experience across the end‑to‑end model development lifecycle, working with large and complex datasets (industry or academic/post‑doctoral experience considered)
• Experience with CI/CD pipelines and modern deployment practices
• Experience working with cloud‑based data platforms and technologies such as PostgreSQL, Teradata, Hadoop, and AWS
• Exposure to fraud, insurance, or highly regulated domains
• Hands‑on experience building and consuming APIs
• A creative, curious, and resourceful approach to problem solving