Life at Dexibit: Predicting experience visitation with Rifky

Every year, Dexibit takes on project interns completing primary research projects in data. Rifky interned at Dexibit for 7 months as part of his Masters in Data Science at the University of Auckland, working closely with Dexibit’s data science team. In his Masters Dissertation, Rifky explored predicting experience visitation for a real world client, a large science museum in the United States.


What inspired you to pursue a Masters in Data Science?

I really liked mathematics in high school so I completed my Bachelor’s degree in statistics. During my first job, I discovered that I enjoyed analyzing data and finding valuable information for decision making. So, I moved from Indonesia to pursue a Master’s Degree in data science in New Zealand.


Tell us about the project you undertook, what did you aim to do?

Dexibit assigned me to a really interesting data science project. I worked with a large science museum in the United States that wanted to predict the number of people that would visit one of their experiences – a tour where people are shown around to see their grounds. The ultimate goal of my research was to predict daily visitation for that tour and to understand what variables influence a visitor’s decision to take part in that experience.

I collected and analyzed multiple data sources – internal data provided by the museum and external data that I sourced myself. For example, the museum gave me daily tour visitation data for the last four years and the external data I collected included the weather and temperature in the area, and Google Trends data which gave me information on Google searches for the venue.


What were the findings and conclusion of your project?

There were many things I found interesting. By analyzing the data, I saw that the tour’s visitation has the same trend as visitation to the museum in general. That meant that I could use the museum’s historical visitation data to predict future tour visitation data. I also found that if it was raining that day, fewer people would visit the venue.

In the end, I created a forecasting model that was able to predict future tour visitation with 83.25% accuracy. I was really pleased with that result.


Rifky (left) reflecting on his project during a retrospective


How did you work collaboratively with the team at Dexibit?

I worked on this project for 7 months and throughout that time I met weekly, sometimes daily, with Radhika, my data science mentor and Data Science Director at Dexibit. I was able to update her on the progress of my dissertation and she provided me with feedback and direction. Angie, Dexibit’s CEO, followed my project closely too. I also worked with Sarah, Senior Success Manager, who kept in touch with the museum in the United States and I asked her a lot of questions, such as how they were using their data.


What did you find most rewarding about the project?

The biggest achievement for me was working on solving a real problem for a client and that I was able to analyze real data. In academia, the work you do can be really theoretical, but with this project – even though I was completing a written dissertation – the client was real. I was able to bring my academic expertise into practice, which was difficult but so rewarding. So I always had to think about what value my project would bring to the client.


What did you enjoy most about being an intern?

That you don’t feel like an intern! Although I only came in twice a week, it made no difference, I was just another member of the team. The people here are amazing and it was great getting to know them.


What were your biggest learnings while working at Dexibit?

While at university I learned the technical basics of data science, but at Dexibit, I learned how to take data and make it meaningful to a real world situation. I also learned non technical skills like how to work with teammates for months at a time, how to communicate effectively with others, and that I shouldn’t be afraid to ask questions.


From left: Rifky (right) reviewing results with the data science team


What are your career ambitions?

I want to continue working in the data science or analytics field. In the future, I hope to work at a start-up or consulting company in an analytics role. I also plan to stay in Auckland for a while before I move back home to Indonesia.


What advice would you give to future interns?

Stay motivated to learn new things. People here won’t expect you to know everything. What’s most important is that you know your data science and statistics basics and that you’re motivated to build on that knowledge. At first, I struggled to understand the data and code, but you’ll get guidance and mentorship, and over time you’ll learn it and are able to deliver a result. 


Learn more about Data Science project internships at Dexibit: