Omar Pardo Gomez worked as a web developer, junior data scientist, and statistical modeler before leaving his home in Mexico City to enroll in the M.S. in data science program through the Data Science Institute (DSI) at Columbia University. Today, the 2019 alumnus is a data scientist at Facebook. Here, he discusses his path to data science, his Columbia experience, and his exciting new job.

How did you become interested in data science?

It was a combination of two things. First, I took some statistics classes, which I enjoyed immensely. I used most of my electives to deepen my knowledge of data science. My love for the field grew so much that eventually my undergraduate thesis focused on an advanced statistics topic. I also started working as a part-time web developer during my senior year and gained programming skills. I enjoyed stats and coding and at the time data science started to emerge as a novel field, so I decided I wanted to follow the path of a data scientist.

You worked for a few years before graduate school. Tell us more about your previous roles.

After I graduated [from Instituto Tecnologico Autonomo de Mexico], I worked as a junior data scientist for a market research firm. Then I worked as a statistical modeler for Banco Bilbao Vizcaya Argentaria, the largest bank in Mexico. In the former, the main challenge was to get the most from small datasets, which required me to master Bayesian methods. For the latter job, the challenge was quite the opposite; since the bank had millions of customers and transactions, I had to develop my big data skills. To analyze the big data, for instance, I used a random forest technique to maximize the bank’s profit by estimating the maximum interest a customer was willing to pay for a personal loan.

Why did you choose to come to Columbia for your master’s degree? Growing up, I barely knew anyone who had studied outside Mexico. As I progressed through college, however, I met professors and students who had studied abroad, and they became my role models. Later, after I graduated, I visited New York and fell in love with the city. I knew then that I needed an excuse to live here and this coincided with the time when I was applying to grad schools. Fortunately, I was accepted at both NYU and Columbia to study data science and you know, Columbia is Columbia, so I accepted its offer.

What were the highlights of your DSI experience?

Being in the program was very cool. The students had different academic backgrounds—math, economics, computer science, statistics, etc.—but DSI did a great job of creating a curriculum that all students benefited from. The highlights for me were learning state-of-the-art techniques about machine learning and deep learning as well as recommender systems and natural language processing. Two classes I enjoyed were Personalization: Theory and Applications taught by Brett Vintch and Applied Deep Learning taught by Josh Gordon. Also, our capstone team worked with Colin Leach and Courtney Cogburn to understand the influence of police violence against unarmed victims by way of analyzing Twitter, an open problem that was challenging in technical and non-technical terms. It was also a case study in how to use data science to have social impact.

Congratulations on your new role! Tell us more.

I will be based at the Facebook headquarters in Menlo Park, and will start in Facebook’s bootcamp, which lasts three weeks. During that time, I’ll be introduced to the different teams at the company and I will end up choosing one. Since data science is a broad field, the duties of teams can be different, some being more technical-oriented and others more business-oriented. What I know for sure, however, is that I will be using the state-of-the-art data science techniques I learned at DSI.

How did DSI prepare you for your work at Facebook?

My work will start with technical duties—statistics, databases, machine learning—which I learned well at DSI. But I will also have to communicate the insights to technical and non-technical decision-makers, and I learned communication skills in both the Exploratory Data Analysis and Visualization courses as well as during my capstone project.

Do you have any advice for current and prospective students, particularly international students?

Don’t be afraid. You will be in a new country, culture, and city, but NYC is a welcoming city. It’s a good place for foreigners to study in and given all its diversity, it is a tolerant and exciting place to live. If you’re looking to turn a new chapter in your life, this is a good place to do it. Try to break away from your studies and get to know the city and the people living here. I also have to say that I dislike the word “networking”. It seems to connote making superficial friendships for the sole reason of advancing your career. Rather, I made true friendships with people I honestly liked and had things in common with. Then, when it came time for me to apply for an internship at Airbnb and a job at Facebook, my friends happily did me the favor of referring me. So get to know the city and make true friends.

— Robert Florida