Teng Zhang
About Teng Zhang
Teng Zhang is a Quantitative Researcher currently employed at Two Sigma in the New York City Metropolitan Area. He has a strong academic background with a PhD in Operations Research from Stanford University and has held various research and data science positions at notable organizations.
Work at Two Sigma
Teng Zhang has been employed at Two Sigma as a Quantitative Researcher since 2021. In this role, he utilizes advanced quantitative methods to analyze data and develop models that inform investment strategies. His work contributes to the firm's reputation for leveraging data science and technology in financial markets. The position is based in the New York City Metropolitan Area, where he collaborates with a team of researchers and analysts.
Education and Expertise
Teng Zhang holds a Doctor of Philosophy (PhD) in Operations Research from Stanford University, which he completed from 2016 to 2021. Prior to that, he earned a Bachelor's degree in Mathematics from Fudan University, studying there from 2012 to 2016. His educational background equips him with a strong foundation in mathematical modeling, statistical analysis, and optimization techniques, essential for his work in quantitative research.
Background
Before joining Two Sigma, Teng Zhang gained diverse experience in data science and research. He served as a Teaching Assistant at Stanford University for nine months in 2017 to 2018. He also held various internships, including a Data Scientist Intern role at Veritas Technologies LLC in 2018, an Applied Machine Learning Intern position at ByteDance in 2020, and a Data Scientist Intern role at Uber in 2020. Additionally, he worked as a Research Assistant at Stanford Children's Health from 2019 to 2020.
Internship Experience
Teng Zhang has completed several internships that have contributed to his expertise in data science and machine learning. In 2018, he interned as a Data Scientist at Veritas Technologies LLC for three months. In 2020, he worked as an Applied Machine Learning Intern at ByteDance and as a Data Scientist Intern at Uber, both for three months. These experiences provided him with practical skills in data analysis, model development, and application of machine learning techniques.