MiddVantage: Exploring Careers in Data Analytics
Watch Episode 6: History Major to a Machine Learning Engineer in Fin Tech with Winnie Yeung ‘15, Machine Learning Engineer at Block (28 min).
Interviewer: Steven Shi ‘23
Video link: https://www.youtube.com/watch?v=4JqYZy1mOao
Winnie Yeung ‘15 is a machine learning engineer at Block in the San Francisco Bay Area, working on developing and deploying Natural Language Processing (NLP) and Computer Vision-related machine learning solutions to improve customer onboarding experiences. She earned her master’s in analytics at the Georgia Institute of Technology and has previously worked at Fidelity Investments and Visa. She has co-authored an NLP course with Mannings Publication and actively contributes to the open-source community by giving talks at PyCon Hong Kong. While at Middlebury, she majored in History and worked with Professor Febe Armanios researching Halal food traditions.
About the Data Analytics series: Data analytics is broken down into four basic types. Descriptive analytics describes what has happened over a given period. Diagnostic analytics focuses more on why something happened and predictive analytics moves to what is likely going to happen in the near term. Finally, prescriptive analytics suggests a course of action. Market watchers project the number of jobs for data professionals in the U.S will increase to over 3 million by 2022. This series includes interviews with many professionals who will share their vantage points on how they use data analytics in their career roles, their paths from campus to career, and career advice they would have for students interested in this career space.
Exploring Careers in Data Analytics is a collaborative series developed by the Center for Careers and Internships and Middlebury in DC with content contributions from members of the Middlebury Professional Network and Middlebury students.