Interview with Thomson Nguyen

Last month I had the chance to talk to Thomson Nguyen, co-founder & CEO at Framed Data, about what got him to where he is today, startups, big data, traveling, and more. Here’s what I learned:

Thomson Nguyen

About Thomson

Thomson spent his undergraduate years at Berkeley. He started as a Bioengineering major before moving on to a Pure Mathematics major with an English minor. Or unemployable math, as he lightly calls it. This consisted of a good deal of logic, set theory, and other pure math concepts. While his classes might not have geared towards been solving real world applications in math, his formative years built a foundation for his later work with computers. Before he got to that point though, he went off to Cambridge for a Master’s degree in computational biology.

Travel (and how to pay for it)

While at Cambridge, Thomson knew that he wanted to travel and explore Europe. One problem though: travel gets expensive.

To pay for his adventures, Thomson started setting up fish and chips websites for local sellers. These owners were often unfamiliar with the internet, but wanted to have a presence on Google Maps, Yelp, and the web.

How do you get started when you don’t have any existing work to show clients?

Thomson made his first website for a fish and chips owner for free. He wowed the owner, and from there his business started taking off. Able to show off his previous work to other fish and chips sellers, he could justify charging for the sites. In 2 months of contract work, he made enough money to travel around Europe for 6 months. As a current college student myself, I’m going to be taking this advice and laterally shifting it to the photography business to fund my upcoming trip abroad. More on that in another blog post though.

Data Science

After graduate school, Thomson went to NY to work at a hedge fund over the summer. The path didn’t seem right though, so when it came time to find a job Thomson went to NYU to research machine learning. There, he learned to derive insights form data via statistical methods. In mid-2011, he went to work for Lookout. Lookout is a security company which helps keep users’ mobile phones safe and private. They also offer solutions for government and enterprise. When Thomson was at Lookout, the idea was to look at Android app data and figure out which apps were malicious. For example, say the average Flashlight application is 70 kb and the average permissions needed is 0. With Android’s rich ontology, apps are already helpfully grouped into specific subcategories. If there are apps that are significantly larger than that, or are asking for more permissions, given a specific distribution curve then it should be flagged for review.

Thomson enjoyed his time at Lookout, but an opportunity came to take a job at Causes that he couldn’t resist. Here, he was a data scientist lead. His day-to-day experiences here consisted of one-on-one meetings with people, product management, and coding. In this exercise in management, he learned how to scale up a team and products. This is the sort of thing that academia doesn’t teach.

Framed Data

After a year and a half, Thomson left Causes to start working on his own company: Framed Data. Framed Data is a predictive analytics application that takes in user data and predicts when they’re going to leave your application, and why they’re leaving. It helps users figure out how they can improve their application, as well as knowing when to reach out to high-risk users.

The idea wasn’t always this polished though. The original idea for the company was to take data scientist’s models and productionize them. The concept was good, and it got Framed Data into Y Combinator Winter 2014. From there, Framed Data pivoted to provide a marketing automation service which helps applications retain their users.

Since getting into Y Combinator, Thomson mentioned his job has transitioned from coding to hiring. Now much of his day-to-day activities are non-technical, and mainly involve sales, business development, customer support, and management.

Data Science Tips and Advice

With his experience in data science, Thomson expanded upon a number of different ways for someone interested in data science to get more involved. One aspect he mentioned was General Assembly courses, which teach you how to become a data scientist over the course of 12 weeks. These types of courses tend to be better suited for non-technical people, though technical people can still pick up a lot from them too. In the course Thomson taught, 95% of the participants graduated from the course with jobs.

Another option for learning more about data science is Kaggle. Here, you compete with teams from around the world on one of the many different data science problems available. It’s a great way to build your data science portfolio on Github. Side tip: your portfolio should consist of code AND plain English talking about the different trends you found. One of the benefits (and also perhaps a drawback) of Kaggle is that it’s graded on a quantitative scale. You are optimizing for a predetermined number. This makes it great for competitions, but in the real world things aren’t always so objective.

Closing Thoughts

Thomson ended our discussion with some closing thoughts on start-ups, career paths, and locations.

Big Companies vs Startups

In his opinion, companies can destroy creativity. Six-figures for a young person starting at their first job makes life too comfortable. Once you’re being compensated at that level, you’re not going to want to take the risk to start your own company.

As an employee at a startup, you’re going to have high visibility to everyone else. You’ll be able to interact with the investors, VPs, CEOs, etc. on a much more regular basis than you would at a big company like Google. Lastly, if you want to work at a startup, consider moving out west. It’s a great place to live, and Framed Data is hiring.


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