Hi, I'm
MS Data Science candidate at Duke University with a concentration in Quantitative Finance. Building regime-adaptive trading systems, credit risk models, and production ML pipelines.
I'm a quantitative researcher and data scientist with a strong foundation in economics and statistics. Currently pursuing my MS in Data Science at Duke University, supported by both Duke Merit Scholarship and Mexico's CONACYT national scholarship.
My work sits at the intersection of quantitative finance, machine learning, and econometrics. I've built an epoch-based leverage pricing protocol for prediction markets achieving +24.2% out-of-sample returns across 884 weekly crypto markets, developed credit risk models analyzing 1.1M loans, and deployed production ML systems processing millions of records.
Beyond research, I lead the Quantitative Finance Club at Duke as Research Director, co-captain the AWS Cloud Club, and co-founded Fiscal Mind - an AI-powered tax advisory platform.
Duke University MS Data Science
Universidad Panamericana BS Economics
LSE Summer Program 2018
Duke Merit Scholar
CONACYT Fellow
Azure Data Scientist Certified
Kaggle Competitions Expert
Research Director, QF Club
Cloud Club Co-Captain
Technical Co-Founder
Duke University - Personal Research
Designed regime-aware multi-strategy portfolio combining copula-based statistical arbitrage, HMM-gated options overlay, and filtered momentum. Achieved 20.6% CAGR with 0.89 Sharpe ratio and 15.4% max drawdown over 2019-2026.
Research Paper — Submitted 2026
Empirical test of epoch-based leverage pricing across 884 prediction markets with 146K observations. Achieved +24.2% out-of-sample returns with 1.49x fee coverage.
Duke University - Fall 2025
Analyzed 1.1M Fannie Mae loans using survival analysis. Built hybrid Cox-XGBoost model achieving 0.998 C-index with 3.25x risk stratification.
Medium - Editor's Selection
Published multilevel logistic regression analysis on timeout effectiveness. Selected for Medium's Boost platform with 10,000+ views.
Read on MediumMulti-strategy portfolio with HMM regime detection, copula pairs trading, and options overlay. 20.6% CAGR, 0.89 Sharpe.
Multi-strategy framework with Markowitz, Black-Litterman, ERC, and HRP. HMM regime detection and CVaR tail risk management.
12th place out of 1,200 teams on Kaggle. XGBoost + GLMM ensemble with hierarchical modeling for tournament prediction.
Hybrid Cox-XGBoost survival model on 1.1M Fannie Mae loans. 0.998 C-index with 3.25x risk stratification.
AI-powered tax advisory platform with multi-agent workflows, knowledge graphs, and 60% API cost reduction.
Interactive analytics platform with custom Added Value metrics, play-type analysis, and expected points from shot selection.
I'm currently open to opportunities in quantitative research, data science, and trading roles. Feel free to reach out if you'd like to discuss potential collaborations or opportunities.
