Get Clay Free →

Hao Jiang

Master Candidate at The University of Chicago

Hao Jiang is a highly skilled individual with a strong quantitative background and extensive knowledge in statistical modeling and machine learning techniques. He gained valuable experience as a quantitative researcher intern at a leading quantitative trading firm in Chicago, where he focused on conducting empirical research on multivariate time series models. Hao has also worked on hands-on machine learning and data mining projects and collaborated with Prof. Matt Daddy at UChicago on high-dimensional statistics topics. He is proficient in coding in languages like C++, Java, Python, and R, and even published his R package called 'DynamicaDistribution' on CRAN during his undergraduate studies in 2013. Hao holds a Doctor of Philosophy in Computer Science from The University of Hong Kong and a Bachelor's in Computer Science from Zhejiang University. With a professional background that includes roles like Software Engineer at Urban Compass, Software Engineer at Google, Quantitative Researcher at J.P. Morgan, and Software Developer at Topcoder, Hao is currently seeking opportunities in Data Science or related quantitative fields.