Quantitative researcher with a habit of going deep—into data, into systems, and into the why behind the models. I work across the stack, from designing features and trading signals to building the pipelines that make them tick.
I like working where ideas get stress-tested at scale—where experimentation meets real-world constraints. Outside of work, I explore machine learning, build tools I wish existed, and occasionally lose hours optimizing things that probably didn’t need optimizing.
This site is a quiet collection of things I’ve built, broken, and learned along the way.