M. Mustafa Arif
About M. Mustafa Arif
M. Mustafa Arif is a Data Scientist at Two Sigma in New York, United States, where he has worked since 2023. He has a background in machine learning and finance, with previous roles at institutions such as MIT Sloan School of Management and the University of Toronto.
Work at Two Sigma
M. Mustafa Arif has been employed at Two Sigma as a Data Scientist since 2023. In this role, he contributes to the development of data-driven strategies, leveraging his expertise in machine learning and financial data analysis. His previous experience as a Data Science Intern at Two Sigma in 2022 provided him with foundational insights into the company's operations and methodologies.
Education and Expertise
M. Mustafa Arif holds a Master of Finance from MIT Sloan School of Management, where he studied Quantitative Finance from 2021 to 2022. He also earned a Bachelor of Applied Science in Machine Intelligence - Engineering Science from the University of Toronto, completing his studies from 2016 to 2021. His academic background equips him with strong analytical skills and a solid understanding of machine learning techniques, particularly in the context of financial data analysis.
Background
M. Mustafa Arif has a diverse background in data science and machine learning. He worked as a Graduate Teaching Assistant at MIT Sloan School of Management for a total of 11 months across two separate tenures in 2021 and 2022. His research experience includes roles as an Undergraduate Researcher and an Undergraduate Research Intern at the University of Toronto, as well as a Machine Learning Engineer at Public Health Ontario. His involvement in collaborative projects at MIT Sloan's Joint Finance Lab with PanAgora Asset Management further enhances his practical experience.
Previous Work Experience
Prior to his current role, M. Mustafa Arif held various positions that contributed to his expertise in data science. He served as a Data Science Intern at Ontario Teachers' Pension Plan from 2019 to 2020, focusing on quantitative strategies and research. Additionally, he worked at PanAgora Asset Management in a joint finance lab initiative with MIT Sloan in 2022. His roles have provided him with a comprehensive understanding of the application of machine learning in different sectors.