Liz Han
About Liz Han
Liz Han is a Quantitative Researcher currently employed at Two Sigma in the New York City Metropolitan Area. She holds a Bachelor of Science in Applied Mathematics from the Massachusetts Institute of Technology and has previous experience in data analysis and machine learning from internships at IBM and Jane Street.
Work at Two Sigma
Liz Han has been employed at Two Sigma as a Quantitative Researcher since 2020. In this role, she focuses on developing and implementing quantitative models to inform trading strategies. Her work contributes to the firm's data-driven approach to investment management. Two Sigma is known for leveraging technology and data science to enhance trading performance.
Education and Expertise
Liz Han studied at the Massachusetts Institute of Technology (MIT), where she pursued a Bachelor of Science in Applied Mathematics from 2016 to 2020. This academic background provided her with a strong foundation in mathematical modeling, statistical analysis, and computational techniques, which are essential in her current role as a Quantitative Researcher.
Background
Prior to her current position, Liz Han gained valuable experience through various internships. She worked as a Data Analysis and Machine Learning Intern at IBM in 2018 for one month in Cambridge, MA. Additionally, she served as a Trading Intern at Jane Street in 2019 for three months in the Greater New York City Area. She also worked as a Research Assistant at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) from 2019 to 2020.
Internship Experience
Liz Han has completed multiple internships that have shaped her career in quantitative research. At IBM, she focused on data analysis and machine learning, gaining insights into practical applications of these technologies. Her internship at Jane Street allowed her to experience the trading environment, where she applied her analytical skills in a fast-paced setting. Her role at MIT CSAIL involved research that further developed her expertise in artificial intelligence and computational methods.