Quantitative Researcher
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I am passionate about utilizing various data to find profitable chances among financial markets. With a solid background in math, coding and finance, plus quantitative researcher internship, I would love the chance to contribute my expertise to the position.
I am a quantitative researcher with experience in high-frequency trading, financial econometrics, and machine learning. I previously interned at KSQUANT, developing high-frequency alpha factors and multi-factor strategies. Currently, I’m a research assistant at Johns Hopkins University, working on Lasso-based nowcasting models and high-frequency MIDAS regressions. I also fine-tune large language models for financial sentiment analysis and serve as a teaching assistant for Empirical Finance.
JHU '26 · M.S.E. in Financial Mathematics: Financial Mathematics