Student Perspectives

Student Perspective

Jimmy Feng

Jimmy Feng

MFE 17

Data Scientist
Uber
San Francisco, CA

Applying Data Science to Finance

I came to Berkeley Haas with a relatively narrow view to becoming a quantitative researcher. The MFE program opened more opportunities to me, such as data science, machine learning, natural language processing—and how they can be applied to finance.

Culture sets Berkeley Haas apart

The Berkeley Haas MFE program gave me the wide variety of useful technical tools you would expect: data analytics, optimization, empirical analysis, and quantitative research. But what you might not expect is the values you learn from the culture at the school.

One value that stood out to me was Confidence Without Attitude. You are surrounded by hard-working, super-successful, and smart classmates and professors, yet everyone is humble and helpful.

Connect with a broad, meaningful network

The Berkeley MFE alumni network is very valuable. Top-tier companies are keen on approaching the community for recruitment and collaboration opportunities both for students and alumni. MFE alumni are very generous to mentor students on career advices and opportunities.

Learning with and from classmates Berkeley Haas encourages peer learning. Coming from a diverse academic and industry background, students are smart, engaged, and at the top of their game.

Members of the Berkeley Haas MFE community are always happy to answer questions or brainstorm solutions to a problem or puzzle.

Projects and practical learning create a track record

Teamwork is essential in the workplace. It makes the end product better. It also makes the culture more human and collegial.

I was on a team that did an industry data research project for Citigroup. By using machine learning to analyze companies’ earnings reports, we generated some very interesting results. It was a great opportunity to be working at the intersection of data science and finance, which is where I work now.

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