Quantitative Researcher | Systematic Research | Statistical Modeling
Ph.D.-trained quantitative researcher with 8 years of experience building, validating, and productionizing statistical and machine-learning models at J.P. Morgan. 4 years of quantitative team leadership with deep expertise in state-space models, factor research, credit and macro modeling, robust backtesting, and high-performance financial data pipelines.
Handcrafted web applications, tools, and open-source packages.
Orthogonalized multi-factor equity strategy combining momentum, low volatility, and volume reversal signals with rolling beta neutralization and MAD outlier filtering.
Productionized statistical library modeling time-varying parameters, latent macro regimes, and multi-asset sensitivities with Bayesian recursive estimation.
High-performance vectorized data processing pipeline processing 20+ years of panel data across 50M+ facilities with out-of-core memory efficiency.
Thoughts on software engineering, architecture, and technology.
Why static linear regressions fail in non-stationary macroeconomic environments, and how recursive Bayesian state-space models adapt to structural shifts.
A quantitative framework for preventing data snooping, adjusting for False Discovery Rates (FDR), and building robust execution simulators.
A collection of frames captured across travels and daily life.
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