José Manuel Peña Mendez: Improving Equity Management Through Machine Learning
José Manuel Peña Mendez approached the Master of Science in Applied Analytics program at Columbia University to develop his skills in machine learning, data science, leadership, and communication, and to enhance his professional skill set in bridging the gap between traditional finance, technology, and quantitative analysis. As a graduate, he’s Portfolio Manager for the International Equity Desk at AFP Habitat, a financial services firm in Santiago, Chile, as well as a developer for and partner in a startup focused on machine learning and neural networks.
Why did you want a graduate degree in Applied Analytics, and what made Columbia the right choice for you?
I was looking for a program that offered both business practices and technology. A lot of institutions provided these, but the Applied Analytics program offered a combination that provided the skill sets bridging the gap between the two. Columbia was also a great opportunity to be in a multicultural city with students coming from a variety of professional backgrounds. Today, maybe more than ever, you’re working and communicating with people from all over the world and Columbia being in New York City offers a diversity that can’t be found anywhere else.
What was the biggest advantage of this program for you?
Learning from faculty who are the best in their field. They are great believers in what they do and offer a way to understand real-world challenges firsthand. Right now, some of the biggest difficulties companies face are finding ways to utilize the data they have as a way to accomplish future growth. In the Applied Analytics program we not only learned how to utilize this data, but how to ask the right questions. I find this really exciting because 10 years ago, companies had trouble understanding this and now they are embracing it.
How have you been able to implement some of the skills you’ve learned?
I gave a presentation discussing what I feel is one of the biggest challenges in the financial industry. In equity management, one of those problems is how to divide the market. By utilizing machine learning and algorithms, we can find better ways to match groups based on seeing how they behave. Here, the novelty was how to apply this to things that already exist to solve current problems and, by doing so, I was able to get a lot of attention from many employers.
How has the program helped advance your career?
Now I am focused on the use of machine learning and deep learning to create value in the Chilean corporate space. At the beginning of this year, I helped found an analytics startup named Project X to leverage the use of advanced analytics in Chile. So far we have been able to develop state-of-the-art deep-learning algorithms to perform social media analysis for brands. We are now also working with a top Chilean telecom to improve clients’ retention through predictive and prescriptive technologies.
What advice would you give to someone interested in the program?
This is a perfect place to hone your skills. I came here with a lot of questions and the Applied Analytics program gave me the tools to find the answers. You will not only learn from great faculty, but also your classmates. I believe a portion of the cohort that enters expects to stay in their respective lanes, but the actual value is being exposed to various sides of the industry. You’re missing opportunities if you don’t branch out!