Crystal finds joy in using big data to develop business strategies and promote growth opportunities. Born and raised in the US, she moved to Indonesia to join Gojek in 2015 and helped drive the unicorn to its success today. She was in charge of data collection and analytics, but also picked up skills involving HR, marketing, and investor relations.
Earlier this year, she left the company for a new adventure. She is now scouting and building up notable startups through her role in Sequoia Capital (San Francisco), and contributing her knowledge at Reforge, which designs e-learning programs on data, engineering, marketing, and growth for experienced professionals. Miles away from Indonesia, Crystal continues to run Generation Girl, a non-profit organization that introduces young Indonesian girls to tech and science through fun and educational holiday clubs.
This interview has been edited for brevity and clarity.
KrASIA (Kr): What ignited your passion for data science and what keeps you going?
Crystal Widjaja (CW): Growing up in an Asian family, my parents had always wanted me to be obedient and to avoid asking too many questions. That left me a lot of time to think and observe my surroundings, especially in the formative years. So it really started out with me being an observant kid.
After high school, I joined the Carnegie Foundation for an internship program, where we focused on education-related research. The research process led to my first exposure to data and even Excel. I helped with basic tasks such as data entry and formatting the math problems that we were researching on.
One day I made a fatal mistake one day by dumping a large amount of data into a pie chart. Later on I was told that there were better ways to visualize such data. So I learned my first major lesson: when presenting data and findings, never use pie charts. And there are tons of visualization tools to use for a meaningful presentation.
I find it super fascinating that data can tell a story in its own way, objective and impartial. So my passion for data science really began with this simple story. And it continues to grow as I work more and learn more.
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