Life as Data Analyst Intern at Bukalapak
What exactly did I expect when I apply for an internship at Bukalapak?
A mathematics student in a start-up company? No one would expect that, well maybe some would, but not my friends and family (hmm). I mean, integrals and technology-based-company? Not that matched. To be honest, I myself had never thought about this possibility when I first began studying mathematics in Universitas Indonesia. Turns out, there is this cool field of work called Data Science. And, with a bit of googling, you may find out that data science combines computer science, math and statistics, and business knowledge. Usually, in its field of works, there are two main jobs involving data science: data scientist and data analyst. And apparently, I got accepted as a data analyst intern at Bukalapak for 2 months. What an opportunity!
How to apply?
I first learned about the internship from the information shared among my classmates, searching for data analyst and data scientist interns at Bukalapak. After I sent my CV, I gave my best in the SQL test and I got interviewed. The interview was mainly about the details on my organizational experience, python, and SQL skills. The thing is, the internship information was actually not really well-known by a lot of people since Bukalapak didn’t list it in their career page. Other data interns had got to specifically ask for the existence of the internship when they came to Bukalapak’s talk show. If you’d like to know whether there is any internship position available, you could send an email to recruitment@bukalapak.com.
Any expectation?
Okay, before we forget, let’s talk about the first sentence in this article. At first, I was expecting that this internship would give me an intern team with this *big-intern-project* to work on. This kind of expectation is based on friends’ stories who had experiences as interns for other companies before. Turns out, it’s nothing like that. The head of data and growth, Tushar, told that the data interns, for the first time, would be treated as actual data employees. We are given the access to the company’s database and actually get the full facility and experience to work. We got paid and daily food plus full experience. Surely, this is far better than I expected.
How’s work?
On my first day, I was placed in Chat squad under Shopping Experience tribe. The squad works on the chat feature in Bukalapak’s website. They deal with its bugs, its performance, its interface, its everything, and how to increase the shopping experience by improving its features, either for buyers or sellers. The squad itself consists of engineers, quality assistants, product managers, etc. It’s cool to be given this opportunity to work with them and actually help with their work.
In this Chat squad, I worked with a data scientist as my mentor. The squad’s data scientists and analysts are responsible for giving the insight, or you could say, data-driven suggestion and decision for better development. This kind of decisions would rely on statistical techniques and comprehension. Other than the Chat squad, I also joined the data team under the same tribe. The team consists of data scientists and analysts from other squads under Shopping Experience tribe. In this team, we share more data-related problems. It’s exciting to be included in a group of data enthusiasts.
To keep growing, there is this some kind of sharing session called Talk with Data every once in a while where data employees could share their knowledge about data. The sessions are also available for other fields of works, such as engineering, etc. It really shows that Bukalapak is really open to growth and always ready to learn something new.
Lessons learned?
In this two months of internship, I learned a lot from Bukalapak. Well, to be honest, you can say that working is about learning. I worked on some projects involving machine learning and statistical analysis. This work involves a lot of learning since data science field keeps growing so new techniques and suggestion will be progressing through time. Other than that, being creative and curious is crucial to see something interesting in data that would bring some exceptional breakthrough for the feature’s improvement. Moreover, communication is also really important since translating data into understandable human words is actually pretty hard. In short, be humble and keep learning. As my mentor said “Accuracy of 50% is like a monkey throwing a coin. But we’re humans so we’d have a way to make it 100%.”
Special thanks to Mas Nashir as my mentor and cool people in Chat squad and Data tribe! 😊
