Fengkai Ye

Quantitative Developer Intern @ Squarepoint Capital

About Fengkai Ye

Fengkai Ye is a Quantitative Developer Intern at Squarepoint Capital, where he has worked since 2022. He has previous experience as a Software Development Engineer Intern at Amazon and various roles in risk analysis and research at notable organizations.

Work at Squarepoint Capital

Fengkai Ye has been employed at Squarepoint Capital as a Quantitative Developer Intern since 2022. In this role, he focuses on developing quantitative models and algorithms to support trading strategies. His work contributes to the firm's efforts in optimizing trading performance and managing risk.

Previous Experience in Software Development

Prior to his current position, Fengkai Ye worked as a Software Development Engineer Intern at Amazon in 2021. During his three-month internship in Vancouver, British Columbia, he gained experience in software development practices and contributed to projects aimed at enhancing user experience and system efficiency.

Experience in Risk Analysis

Fengkai Ye served as a Trading Floor Risk Analyst (co-op) at Ontario Teachers' Pension Plan from 2019 to 2020. In this capacity, he analyzed trading risks and supported the risk management team in making informed decisions. His role involved assessing market conditions and evaluating potential impacts on the trading portfolio.

Research Assistant Roles at University of Toronto

Fengkai Ye held two positions as a Research Assistant at the University of Toronto. His first role lasted from 2018 to 2019 for six months, and he returned for an 11-month period from 2020 to 2021. In these positions, he assisted in academic research projects, contributing to data analysis and the development of research methodologies.

Education and Academic Background

Fengkai Ye earned a Bachelor of Science degree from the University of Toronto, specializing in Mathematical Applications in Economics and Finance and Computer Science. His studies spanned from 2017 to 2022, providing him with a strong foundation in quantitative analysis and software development.

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