Life After LEAD

We catch up with one of our former LEAD Scholars.
By Bernease Herman, ’13

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Last December, I returned to (a surprisingly snowless) Ann Arbor for my little sister’s graduation from the Ross School of Business. High in the stands at Crisler Arena, I speculated on which dot in the crowd was my sister. I had a lot of time to think — commencements aren’t known for their nonstop entertainment value.

My little dot in the crowd was graduating with a bachelor’s degree, then returning for her master’s degree in accounting next year. My little brother is not far behind — now in second grade, he knew “Michigan” was a university before even learning it was a state.

We became a Michigan family when I received the LEAD Scholarship from the Alumni Association and decided on U-M. I had been debating between Michigan and Stanford. Choosing Ann Arbor allowed me to graduate debt-free, attend a specialized degree program, and connect with a cohort of other LEAD Scholars doing amazing things. By graduation, I had achieved my goals.
After high school, I planned on becoming an actuary — an analyst of insurance risk and uncertainty like Ben Stiller’s character in “Along Came Polly.” I switched to interning on trading floors in New York City before I discovered my love for computer science during my senior year.

I worried I was too late but had the chance to make the transition. I turned down my investment bank offer to work at Amazon as a software engineer; moved to Seattle; had a visit from another former LEAD Scholar, Briana Lung, ’15; took a new job doing machine learning and data science research; and learned a ton about myself.

My team at Amazon controlled when and how much of the company’s 200 million products to order for the warehouses. Optimizing these orders is a huge mathematical problem, so I used many skills learned in my mathematics and statistics classes.

I’m now a data scientist at the University of Washington eScience Institute. We use advanced math, statistics, and computer science techniques to solve research problems across scientific fields. Math is an even larger part of this work, although I still write plenty of code. I love what I do! As if probability, research environment, and working on cool things like artificial intelligence weren’t enough, I’m also obsessed with the the innovation and startups that we work with. I can definitely see myself headed that way in the future!

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