My internship at Tapad has officially come to an end last week, after I gave a final presentation of my project (see the intro video below). It’s been a very memorable and rewarding summer. I not only learned about the latest technological development and application of machine learning and big data, but also got to experience the industrial work style and start-up culture.
A few takeaways from this summer experience:
1. Big data machine learning is such an intriguing field that I never get tired of learning.
Starting from day one at Tapad (even before that, starting from my interview), I was fascinated by the problems AdTech tried to tackle and the big data aspect. Tapad has a very unique position in AdTech: while Google and Facebook together capture 2/3 of the whole $60B AdTech industry given their large user base, Tapad captured a niche of cross-device solution without relying on log-in data completely. With high respect of data privacy and user protection, Tapad takes advantage of real time big data and advanced machine learning in order to deliver online ad to the correct audience.
While I was doing my internship in the past 2 months, I was also taking the AI nanodegree from Udacity to learn about computer vision, natural language processing, and logistic and planning. These AI tools are highly applicable in AdTech, providing insights about user preference and behavioral pattern.
In addition to current projects, the data science team at Tapad keeps close track of the latest research development in machine learning algorithms and tools. A colleague coming back from KDD 2017 conference shared her notes about talks in recommendation system, causal inference, and counterfactual risk assessment. The data science team members share interesting articles and GitHub repositories in group chat frequently and discuss about recent news in the industry.
2. Colleagues you wanna chat with.
My 8-week stay at Tapad is very pleasant thanks to my friendly and humorous colleagues, both on the data science team and other teams. People that I worked with are patient, ready to answer my most basic questions and provide detailed instructions. During my farewell party, while we chatted about random topics and enjoyed Margarita, my colleague gave me a lovely handwritten farewell card! I was very grateful to have them supporting and helping me in my early career.
I also got to know people outside the data science team, mostly developing from a small chat in the kitchen area to more in-depth discussions later on. For example, there is only one engineer who plays Dota2 while the rest of MOBA players in the company are all LOL fans. So naturally, the Dota2 guy and I got to know each other very quickly (haha) And there is another full time employee who joined Tapad the same day as I did, and he is a huge fan of comics and anime, so naturally, as a comic fan myself, I got to chat with him about comics a lot. And there are also people who are super good at Foosball, who traveled to South Africa, who have a passion for Whisky. The company, despite its small size, has a wide diversity of people, and each one has a ton of interesting stories.
3. Small is Big.
Start-up companies are mostly small in size. Knowing most people in the company by their first names become quite practical, which not only brings in some sort of comraderies, but also encourages transparency and accountability.
As an organization gets larger and layered, responsibility may get diffused and individuals’ influence may get diluted as well. An engineer may be part of something grand, such as the Google Search Engine team, and make a huge influence on the world. Yet at individual level, it could get more and more difficult to directly visualize how much impact one person has made to this grand project. At small companies, things tend to be faster and more straightforward as the organizational structure is less complex. We have a better idea what we build, how it is deployed, and what result it generates. As a result, we know more clearly that what we are working on is making an impact.
As an intern, I was very pleased to be able to join planning meetings and talk directly with data science veterans. Besides focusing on my specific area, I also got exposed to the big picture of the company and the whole data science industry, and learned about the current trend, future roadmap, and market landscape. Such high level participation enables me to think bigger and wider, which is essential for long term career development.
Overall, I will continue learning the Force of Data Science and hope to make a big impact using the Force.
May the Force be with you.