New York, NY
Tell us a bit about yourself.
I grew up in Silicon Valley but wanted to experience something different for college, so I went to Columbia University for undergrad. It seemed hard to beat an Ivy League school in the heart of New York City. I was interested the practical application of math. Being in the world’s biggest financial hub in the midst of a quantitative finance revolution, I gravitated toward operations research with applications to finance.
I interned at Moore Capital Management, a macro hedge fund, the summer before Lehman Brothers collapsed. To their credit, Moore Capital weathered the crisis very well and were able to make me a job offer. I joined a great four person relative value investment team in the summer of 2009 and have stuck with them since. I build quantitative risk management and idea generation tools, while also contributing to more qualitative, strategic aspects of decision-making.
What initially attracted you to the Master of Information and Data Science?
A Bloomberg terminal is a data fire hose, so quantitative finance has been a great laboratory for data exploration and self-education. However, I wanted to fill the gaps in my self-taught knowledge and have a structured environment to learn state of the art data science techniques.
Why did you choose the UC Berkeley School of Information?
I was attracted to the UC Berkeley School of Information because of their cross-disciplinary mandate and ties to Silicon Valley. The I School is not just for computer scientists or statisticians but also for a wide range of people who are looking to improve decision-making and problem solving by using better information. I was also excited about UC Berkeley as a conduit for cutting-edge ideas coming out of Silicon Valley.
Ultimately, I was looking for a structured environment to fill out my data science skill set. The MIDS program allowed me to do this flexibly while continuing to pursue my career.
What surprised you the most about the program once you started taking classes?
I was surprised with how other students’ attitudes and approach to data problems are different from my own. That diversity of professional and academic backgrounds inspires fresh thinking about your own challenges. I have also been impressed (though not particularly surprised) with how well the live online classroom setting works. With simultaneous audio, video, and text chat I think it is a better forum for group discussion and learning than an actual classroom.
What do you hope to accomplish upon graduation?
I get excited about using data to improve real world decision-making. I want to use my education to improve or create a company that uses analytics as a tool to solve hard problems.