ML Engineer - Credit Scoring & Risk Models

Role overview Prototype and evaluate machine learning features for credit scoring and leasing risk workflows. The work uses synthetic data for demonstration and focuses on model quality, clear evaluation, and making product decisions easier to explain.

Responsibilities - Develop and test risk-related features using synthetic datasets. - Evaluate scoring model performance and present results through clear, readable metrics. - Work with product colleagues to make model-driven decisions more explainable.

Requirements - Python experience and applied machine learning skills. - Solid understanding of model validation fundamentals.

Nice to have - Knowledge of credit risk. - Some experience with machine learning operations.

Benefits and work setup - Full-time, remote work from France. - Opportunity to tackle applied data problems and collaborate directly with product colleagues.