Senior Data Scientist - Credit Risk Modeler

📋 Description

• Take ownership of the existing model (tree ensembles / gradient boosting), retrain it, and
• Evaluate performance (AUC-ROC, F1, probability calibration) and segment risk levels A–F aligned
• Calculate dynamic credit lines and expected loss (risk exposure), integrating score, potential, and
• Package the model under the MFL framework (PyFunc, model_card, tests) for productionization.

🎯 Requirements

• Proven experience in credit risk / scoring models and supervised machine learning.
• Python (scikit-learn, XGBoost), statistics, model validation, and MLflow.
• Understanding of risk metrics (PD, expected loss, exposure).

🎁 Benefits

• Experience in financial services, credit bureaus, or commercial credit portfolios.
• Experience developing AI agents / agentic infrastructure (e.g. Mosaic AI Agent Framework, agent