Executive Q&A with Hong Tsui, VP of Data Science and Finance at Jumpshot
Today we got to know Hong a bit better. A modern day renaissance man, Hong has travelled the world, was an adventure guide for almost 10 years, holds three degrees, and has some solid life and career advice for those just starting their career.
Q: How long have you been with Jumpshot?
A: Two and a half years.
Q: What initially drew you to Jumpshot?
A: Deren (Jumpshot’s CEO), and I have worked together for almost 10 years. So when he was asked to join Jumpshot to run this new company, he invited me to come join the team.
Q: What is your technical background? How’d you come to be the VP of Finance and Data Science?
A: I’ve gotten similar questions since I was a child. I have two types of degrees. My economics degree is considered an art, and my two engineering degrees are considered a science. But I never distinguished between the two in my head. I always thought the two areas of study went together as they’re both analytical and numbers driven. However, from the outside perspective in both the academic and professional world many have seen them as separate.
I’ve always enjoyed math. I always thought it was a language I could understand and express clearly. Looking back, it made sense that I pursued mathematical degrees. To me, math is used to describe the laws of nature, whereas economics is used to describe human behaviors in a mathematical way. To this day I still use math and its principals to help make sense of both.
Q: What aspects of data science interest you the most? What sorts of projects do you most enjoy?
A: In general, the projects I enjoy the most are when we use numbers to make strategic decisions. That’s general, but I love being able to translate between the two. I like to go back and forth between the black and white of mathematics, and then back into the gray area of strategic thinking. People like to think those are opposing forces, but I don’t believe that.
Like anything you study, the more you know the more you realize you don’t know. Data science is like that. It constantly shows the limit of data and math, which is when the strategic thinking needs to fill in. That’s what I love.
Q: Are you working on any projects that you’re especially passionate about right now?
A: One of the projects we’re working on is trying to auto-identify all of the interesting touchpoints on the world wide web. As you can imagine, we have billions of URLs within our data. Our objective is to identify the different URL sets, so we can say “this set of URLs is search, and this set is a product view, and this set is a conversion,” across all the different domains and languages within those domains.
Q: What are some of your favorite things to do outside the office?
A: All things outdoors and physical. After college, I was an outdoor guide for 10 years. River rafting, climbing, bicycling; everything you can imagine. Anything that combines being in a new place, new environment, and physical exertion, I love.
Q: What’s your favorite place you’ve ever travelled to?
A: That’s tough, and I get asked this a lot. From a spiritual perspective, looking at the body and mind, I’d say Tibet and the greater Himalayan region. From a pure nature and beauty perspective, it would be the Southern Island of New Zealand. Then from a culture and food perspective, Japan has to be up there. Specifically the region around Kyoto.
Q: What advice do you have for someone just starting their career in a technical role?
A: Concentrate on interpersonal skills more than technical skills. Anybody who has studied or has a technical career, they always focus too much on the technical skills. It doesn’t matter if you’re a doctor, lawyer, or a data scientist, it’s your interpersonal skills that will further your career.
Q: What are some lessons you learned early on in your career that still guide you today?
A: Communication. Look people in the eye. One thing I learned in my early years is that numbers don’t lie but people do, which means that the interpretation of the numbers is just as important as mathematical calculations.