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Lauren Yu

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Born and raised in China, Lauren attended State University of New York at Buffalo in Amherst, NY, where she graduated summa cum laude with a B.A. in Mathematics and minor in Political Science. Always eager to apply her knowledge to real-world problems, Lauren participated in three quantitative social science research projects as an undergraduate. Each of the three projects not only taught her to analyze complex social issues with a hypothesis-driven approach, but also exposed her to the power of data analytics. Working extensively with both R and Python, Lauren witnessed how data analytics revealed insights where traditional social science theories failed to do so. She thus set forth to take more programming and statistics courses, including a few graduate-level ones.

The presentation of data fascinates Lauren as much as its examination. A self-taught graphic designer, she believes an insightful analysis is never complete without an equally articulate visualization. Lauren transferred her design skill to good use during a recent internship at China Merchants Bank, where she not only developed algorithms to effectively cleanse and process over 4 gigabytes of data, but also visualized her analysis through a corporate relationship network. Through this experience, Lauren familiarized herself with analytics application in commercial banking, especially in credit risk management. However, she is also excited to learn about data-related opportunities in other industries, including management consulting and market research.

Thrilled to be a member of MSiA’s 2017 cohort, Lauren seeks to develop a well-rounded skill-set consisting of both technical expertise and business acumen. An aspiring data scientist with an interdisciplinary background, she is particularly interested in applying analytics to extract human insights. Whether it is customers, users, or voters, she wishes to help organizations better understand their target group and thus make more informed decisions.

In her free time, Lauren enjoys Argentine tango, jogging and reading.