Data Scientist specializing in credit risk modeling and energy market analytics, with an MS in Data Science (Statistics Track) from Rutgers University.
I build end-to-end ML pipelines - data → modeling → calibration → monitoring - and I'm especially interested in problems where statistical rigor and domain context both matter: credit underwriting, energy markets, and policy analysis.
Credit Underwriting & Decisioning System Production-style underwriting pipeline: calibrated PD model → scorecard (PDO) mapping → decision/reason codes → PSI drift monitoring, built on a fully synthetic, compliance-documented credit bureau dataset.
Energy Market Forecasting & Policy Impact Analysis Forecasts U.S. state-level electricity generation mix (50 states, 1990–2023) using CLR-transformed compositional time series and per-state VAR models - including an honest benchmark against a persistence baseline.
- Data Science Intern, Synergy Resources - built a credit underwriting pipeline (AUC 0.87) supporting a 50K+ account portfolio
- Statistics Grader & Mentor, Rutgers University (2 years)
- Certifications: Bloomberg Market Concepts (BMC), Financial Statistics & Risk Management (FSRM)
Python XGBoost LightGBM TensorFlow scikit-learn statsmodels pandas · AWS (S3, EC2, Lambda) Docker · SQL