I build at the intersection of data, economics, and machine learning, focused on quantitative finance and applied ML.
Open to: Data Science · Quantitative Research · ML Internships
Pairs-trading engine with Kalman-filter dynamic hedge ratios and walk-forward OOS validation over ~14 years — 1.02 out-of-sample Sharpe, survived Deflated Sharpe Ratio correction for multiple-testing bias.
Python statsmodels pytest
LoRA fine-tune of Qwen2.5-3B for a low-resource language — +8pp on Belebele (22→30%) and 4× SIB-200 macro-F1 vs. few-shot. A native-authored eval harness exposes chrF++ as a poor quality proxy (Cohen's κ = 0.000).
Python PyTorch LoRA
S/T/X/R/DR meta-learners for treatment-effect (CATE) estimation on Criteo's 14M-row benchmark, with Qini/AUUC metrics from scratch. The X-learner beats a response-model baseline by 28% on top-decile targeting, exposing outcome ROC-AUC as the wrong objective for incrementality.
Python EconML scikit-uplift
3-state Gaussian HMM (EM) driving VaR/CVaR estimation with 94.7% empirical coverage on SPY. Performance-critical path implemented in C++.
Python C++ NumPy
Character-network and sentiment analysis across 134 episodes of Suits (VADER, spaCy, PageRank, LSTM, XGBoost) with an interactive Streamlit dashboard.
Python spaCy Streamlit
Languages
Machine Learning / AI
Data Science / Statistics
Visualization
MLOps / Tooling
Frontend / Web
