Choose your coursework that takes you where you want to go
The opportunity to apply my skillsets in a new division at Goldman Sachs was something I couldn’t turn down. And being able to apply my data science skills in developing new products makes this an exciting opportunity.
I came to the MFE with a fair amount of financial experience. That inclined me to focus my studies on practical projects and classes that would allow me to implement models and strategies in real-world settings. I wanted to see the business impact of my work.
Top quality faculty befit a top quality program
The Berkeley Haas MFE places you in the classroom with outstanding faculty members, many of whom are industry professionals.
Starting with the statistics refresher that was offered before MFE classes started, through his Empirical Methods in Finance class, Professor Martin Lettau taught and then built on fundamental concepts, like time series, that I rely on in creating forecasts.
Professor Laurent El Ghaoui’s class in Financial Data Science was my introduction to what finance will look like in the future. He covered all of the theoretical aspects of machine learning using examples of how these approaches are playing out in industry.
Where I really got excited was in the elective Building Machine Learning Systems: Tools, Platforms, and Financial Applications taught by Carolina Galleguillos. This hands-on class gave us the opportunity to implement theories, mentored by people in the industry.
Learn and lead the way in data science
I appreciated being taught in a business school, especially one so close to Silicon Valley and to companies innovating in the finance industry.
There already are lots of Berkeley Haas MFEs working in data science roles at tech companies such as Google, Uber, OpenDoor, and Facebook. The financial sector is also increasingly looking at growing their data science teams, and Berkeley Haas alums will be leading the way.