Vasilis Oikonomou
About Vasilis Oikonomou
Vasilis Oikonomou is a Quantitative Researcher at Two Sigma, where he has worked since 2019. He holds a Bachelor of Arts in Statistics from the University of California, Berkeley, and has previous experience in machine learning and data science internships.
Current Role at Two Sigma
Vasilis Oikonomou serves as a Quantitative Researcher at Two Sigma, a position he has held since 2019. In this role, he focuses on leveraging real-world data to address challenges within the investment management sector. His work involves exploring the relationship between conceptual hypotheses and quantitative representations, contributing to the firm's research initiatives. Oikonomou collaborates with colleagues, emphasizing teamwork and knowledge sharing in a stimulating environment.
Previous Experience in Quantitative Research
Before his current role, Oikonomou interned as a Quantitative Research Intern at Two Sigma in 2018 for two months. This experience provided him with insights into quantitative analysis and investment strategies. Additionally, he worked as a Machine Learning Intern at UnifyID in 2017 for three months and as a Data Science Intern at Workable in 2016 for one month, both of which enhanced his analytical skills and understanding of data-driven decision-making.
Education and Expertise
Oikonomou studied at the University of California, Berkeley, where he earned a Bachelor of Arts (B.A.) in Statistics from 2015 to 2019. His academic background includes a strong foundation in statistical methods and data analysis. He also completed his high school education at the Hellenic American Educational Foundation Athens College - Psychico College. His educational experiences have equipped him with the skills necessary for his research and analytical work.
Teaching Experience at UC Berkeley
During his time at the University of California, Berkeley, Oikonomou served as an Undergraduate Student Instructor from 2017 to 2019. In this role, he contributed to the academic development of fellow students, reinforcing his understanding of statistical concepts while fostering a collaborative learning environment. This experience highlights his commitment to education and mentorship in the field of statistics.