I am a Data Scientist focused on turning data into reliable decision support through sound problem framing, careful evaluation, and interpretable machine learning. My current interests include predictive modeling, customer analytics, risk modeling, and production-ready data products.
- Data Science: EDA, feature engineering, statistical inference, temporal validation, model interpretation
- Machine Learning: regression, classification, clustering, calibration, imbalanced learning
- Tools: Python, SQL, Pandas, NumPy, scikit-learn, XGBoost, SHAP, MLflow, FastAPI, Docker


