Victoria Li graduated from UC Berkeley in 2015 with a double major bachelor’s degree in Applied Math and Statistics. She wanted to build on her quantitative background in tech and data science, and so began to pursue a career in the “fast-paced and upbeat” financial industry. For Victoria, The Berkeley MFE was the right program to kickstart her career, broaden her financial knowledge, and apply her quantitative methods to a new career of interest.
Before making the transition to finance, Victoria interned as a data scientist at Facebook’s major media buyer, Brand Networks, LLC, where she devoted most of her time to analyze Facebook advertising pricing and performance data. In addition, she worked as a data science team leader at a San Francisco startup designing essential system algorithms.
Currently, Victoria is working with a team of four students on an Industry Project involving sentiment based trading strategy as part of an MFE elective. They have utilized Apache Spark to process and analyze nearly 20 Terabytes of web news sentiment data.
“This project has given me deep exposure to data science, where my interest lies. The Berkeley MFE definitely has provided me with enormous insights into the Fintech industry today, and a competitive edge in finance by leveraging my understanding of big data,” said Victoria.
She gained further experience in Pyspark Machine Learning Pipeline as well as performing Data Frame/RDD based data analysis. To accommodate the challenges of her industry projects she is taking Scala programming courses in her spare time to expedite her computation speed.
Beginning in October, Victoria will work as a Quantitative Investment Analyst at BlackRock.
“The Berkeley MFE has an exceptional student body. All students come from diverse background and are extremely passionate about their studies. I enjoy being surrounded by brilliant people and so, the Berkeley MFE is the place to be. There is a lot to learn from each and everyone of us.” -- Victoria Li, MFE 2017