Projects

Side projects, mostly recent.

/01
Who actually defaults?
CatBoost SHAP AI Governance
CatBoost vs. XGBoost vs. LightGBM on UCI Credit Card Default data, optimized for recall on the minority class. SHAP explainability and EU AI Act compliance documentation built in.
Recent payment status dominates. Demographics contribute almost nothing.
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/02
Should you call this customer?
Causal Lift A/B Testing Power Analysis
Most marketing analytics measures who converted, not who converted because of the call. Built on the UCI Bank Marketing dataset with covariate adjustment, segmentation, and SHAP explainability.
Prior contact lifts conversion 2.5x; holds after covariate adjustment
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/03
Should you swing on a 2-0 count?
Markov Chains Sabermetrics MLB
A softball coach told me my whole life not to swing on a 2-0 count. Capstone thesis project using Markov Chains on MLB data to test whether he was right. He was. This is also how I ended up in data science.
He was right. The Markov chains agreed. CLU · 2016–2017
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