I will build a credit risk prediction model using python

Need help assessing loan default risk?

I build credit risk models in Python to identify high-risk loans, understand key risk drivers, and support data-informed lending decisions.

What I offer: Data cleaning and preprocessing; default-risk analysis; Logistic Regression and XGBoost modeling; model evaluation using AUC-ROC, precision, recall and confusion matrix; risk-driver analysis; risk segmentation; actionable recommendations; clean, reproducible Python code.

Why work with me?

In a recent project, I analyzed 2.25M+ loans and found that a selective verification policy could improve estimated net value by $29.4M on a 300K-loan sample, using predictive modeling, survival analysis and causal inference.

With a statistics background, I focus on rigorous validation, appropriate assumptions and honest reporting including model limitations, not just numbers that look good.

You'll receive: analysis, code, model results, visualizations and a clear summary.

I work with loan, credit and default-risk datasets. Message me before ordering with your dataset and business goal so I can recommend the right approach.