Lakshay Sapra
About Lakshay Sapra
Lakshay Sapra is a Quantitative Researcher at Squarepoint Capital in the New York City Metropolitan Area, specializing in automated data solutions for alpha generation. He has a background in Electrical and Electronics Engineering and Financial Mathematics, along with experience in international market collaboration and major data vendors.
Work at Squarepoint Capital
Lakshay Sapra currently holds the position of Quantitative Researcher at Squarepoint Capital, having joined the firm in 2023. He has previously worked at Squarepoint Capital in various roles, including as a Quantitative Researcher Intern in 2022 and as a Software Engineer focusing on Data Science and Engineering from 2017 to 2021. His experience at Squarepoint Capital spans multiple locations, including significant time spent in the New York City Metropolitan Area and Singapore.
Education and Expertise
Lakshay Sapra earned his Bachelor's of Technology in Electrical and Electronics Engineering from the Indian Institute of Technology, Delhi, completing his studies from 2013 to 2017. He further advanced his education by obtaining a Master of Science in Computational Finance from Carnegie Mellon University in 2022. His academic background supports his expertise in developing automated data solutions that leverage statistics and machine learning for alpha generation in finance.
Background
Lakshay Sapra began his education at Ahlcon Public School, where he studied from 2008 to 2013. His professional journey includes a summer internship at VMock in 2016, where he gained initial exposure to the industry. He has accumulated extensive experience working with major data vendors such as Bloomberg, Refinitive, and ICE, focusing on financial and alternative datasets.
Achievements
Throughout his career, Lakshay Sapra has gained international market exposure by collaborating with quantitative desks globally during his tenure at a systematic hedge fund. His specialization in developing automated data solutions has positioned him as a valuable asset in the field of quantitative finance, particularly in the application of statistics and machine learning.