A career move with impact
In my first job at CASHe I explored how artificial intelligence can be used on behavioral datasets to push the boundaries of financial inclusion outside the formal banking system.
To advance in my career, I needed to be adept with the tools and modeling principles used in sophisticated mathematical modeling and AI-based techniques.
Unlike other programs, the Berkeley Haas MFE curriculum has kept pace with the trends in finance, from data science to artificial intelligence to natural language programming.
The quality of my classmates was an intangible benefit. They are an ingenious, innovative, and competitive group. On team projects, we played to each other’s strengths and each of us pushed the other to up their game.
My classmates were a great network in themselves, plus you have the MFE alumni network. You have instant access to people working at top-notch banks and tech companies in path-breaking jobs.
Academics fine-tuned and flexible
The academics have been fine-tuned to address the skills needed in a wide range of career paths, from trading and quant research to data science.
Statistics taught by Martin Lettau, Data Science with Laurent El Ghaoui, and Eric Reiner’s class in Derivatives, all stand out for the excellence of the teaching.
I appreciated the way Eric Reiner approached problem-solving. He is more than a teacher; he is a friend.
The program gave me the flexibility to do five separate industry projects. Each was distinct and they all contributed to landing my internship with Moody’s Analytics.
An award-winning internship
At Moody's I used NLP to scrape data from many sources—newspapers, annual reports and disclosures—to create a tool to evaluate a company’s risk to climate change.
It was exciting to develop a new tool on a topic that I knew little about—climate change—that is having such a big impact on the world.
It was also cool to win award for this, even though I was competing against actual Moody’s employees. That felt good!