Eugene Tang, 28, Class of 2016
Tang earned his bachelor’s degree in computer science from Princeton University, while also fulfilling requirements for the undergraduate certificate at the Center for Statistics and Machine Learning (CSML) and the engineering and management systems certificate at the Department of Operations Research and Financial Engineering. In 2020, he earned a master’s degree in information and data science from the University of California, Berkeley.
Currently, Tang is a quantitative researcher at Citadel, a hedge fund and financial services firm.
“At Citadel I take a quantitative approach towards investing,” Tang said. “We look at various datasets to make trading decisions - there is a lot of rich data that's out there in the world. Much of my work involves modeling - creating models with the data to tell a computer how to make trades.”
In a previous position, Tang worked as a quantitative software engineer in natural language processing at Two Sigma, a hedge fund firm known for its use of artificial intelligence, machine learning, data science and distributed computing. In his work at Two Sigma, Tang processed and analyzed data sets from the news. He joined the company after he graduated from Princeton.
“Natural language processing helps analyze textual datasets, such as news articles, to see if there is a connection between that and stock market prices,” he said about his work.
Between his stints at Two Sigma and Citadel, Tang also worked as a part-time data analyst at Giving Assistant, a then-existing shopping start-up business. He also contributed to Towards Data Science, an influential online magazine for sharing data science concepts and ideas. For example, he wrote an article about how he created an image-to-text algorithm that generates captions for New Yorker cartoons.
Tang worked on a natural language processing system for his senior thesis to find signs of depression on Twitter. The project also fulfilled his CSML independent work requirement. Christiane Fellbaum, a computer science professor, served as his thesis advisor.
“At the time of the project, it was a period where people were becoming more aware of the importance of mental health, which inspired the project,” he said.
On the CSML undergraduate certificate, Tang said the curriculum gave him a solid foundation to learn more complex topics.
“The field of machine learning has been changing so rapidly. What was the state-of-the-art when I was in college is no longer the case. And with the certificate curriculum laying an excellent foundation, that's helped me quickly pick up the new stuff,” he said.
“I think Princeton does pretty well, in general, in teaching the foundation of topics,” he continued. “You learn, for example, why we approach linear regressions a certain way.”
Tang plans on staying in industry in the foreseeable future. But he would like to try his hand at teaching, which he enjoys.
Currently, Tang enjoys running and hiking and trying to solve the New York Times crossword puzzle.