Qingnan Tang is a seasoned researcher with expertise in quantitative analysis and machine learning. Currently serving as a Research Associate at WorldQuant since September 2019, Qingnan previously worked as a Quantitative Researcher Intern focusing on FX Options at J.P. Morgan and contributed as an NLP researcher at Amaris.AI Pte Ltd. With an impressive record of achievement, Qingnan earned the title of Kaggle Competition Master during involvement with Kaggle from December 2016 to December 2018, competing in various data science challenges. Qingnan's academic credentials include a Doctor of Philosophy (PhD) in Statistical Physics from the National University of Singapore and a Bachelor of Science in Physics from Shanghai Jiao Tong University. Additionally, experience as an HPC cluster administrator further complements Qingnan's strong technical background.
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