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Dissecting Data in the Big Apple

by Luyang Han, 25.10.2018
Work at the zkipster NYC office (photo credit: Luyang Han/ETH Zurich)

In May 2018, I joined the Swiss company zkipster as an intern on a machine-learning project to make show-up predictions for invited guests. zkipster is an event management software company that provides services such as online invitations, guest seating and event check-in. It aims to provide a global platform to make event planning intuitive, guest check-in fast, and event analysis insightful. Incorporated in 2012, zkipster has checked in over 15 million guests at various events around the globe in over 100 countries.

Currently working remotely from Zurich, I am responsible for researching and developing algorithms and models to predict the probability that an invited guest will attend an event. By the end of the internship in December 2018, the goal is for me to present the best model to zkipster’s engineering team.

As part of the ETH Studio New York whereby students solve a challenge set by leading organizations in the digital field, I had the opportunity to travel to the New York office of zkipster for 10 days to further explore the event management industry. I gained additional insights on the operations of the company, with the aim of providing better services to professionals worldwide.
Photo credit: Luyang Han/ETH Zurich
I am a Master student at ETH Zurich who was raised in China and completed my Bachelor studies in the United States. During that time, I visited New York City several times and was blown away by its scale and grandeur. However, nothing prepared me for the experience of working in an office located on the 23rd floor of a building on Broadway, which was unique. Having had limited working experience it was exciting to work in such a professional environment for the first time. I also felt that being on location was completely different from working for the company remotely.

In addition to working on my current project, I was able gain special insights from zkipster’s Client Relation team. They demonstrated product features in details to me, and in turn, I explained the details of what I had been mandated to work on. Their explanations helped me get a deeper understanding of the nature of data in the event management industry, which enabled me to better identify potential outliers within the dataset.
Being a Data Science Intern at zkipster enabled me to work with hard data from the real world. This was totally different from the data from a course project; it was more self-driven and required me to perform a larger amount of exploration into the background of the data. The most useful insights for me there have to do with insider knowledge relating to the product and the industry. These will provide me with valuable long-term perspectives for solving these types of challenges.

For me personally and professionally, it was a great experience to talk to people who are familiar with the latest products and interact with clients on a daily basis. I got to know particular questions raised by clients, and learned what solutions zkipster would work towards in response. In addition, the trip motivated me to further think about the challenges and opportunities faced by start-ups beyond the field of Data Science.

Having studied in different countries encouraged me to explore different cultures and to try a variety of things. The trip to New York allowed me to learn about life as a professional working abroad in one of the world’ most exciting cities. Most importantly, I have since then been better able to apply what I learnt in lectures to practical problems, providing proof that this experience broadened my understanding of Data Science with regards to the real industry.

About the author

Luyang Han is a Master of Statistics student at ETH Zurich and is working with zkipster, a start-up company collaborating with the ETH Studio New York, as a Data Science Intern from May to December 2018.
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