Like a lot of other Data Schoolers, I had several years’ experience working elsewhere before joining the program. As a result, I was quite pragmatic about keeping my expectation in check. I know too well that “No job is perfect”. To my surprise, the first week was a lot of fun with great memories, prompting me to think about why there was such a huge difference between the Data School and my previous job, where I worked as a Global Marketing Coordinator in Japan.

Doing what I love vs Doing something for the company

The largest difference between the Data School and my previous job is that I get to do what I love. I talked and sold this story a lot during job interviews, but I really mean it. While ‘passion’ is such an overused word in the Western world, it is more or less a childish pipe dream in Japan. Many of my Japanese friends and colleagues have come to accept that ‘Work isn’t fun’. According to Japanese work ethics, work is meant to be tough and stressful. That’s how you grow up and mature. The training I received wasn’t technical but to foster the love and loyalty to the company and to look ‘professional’ as a businessman. Even if I like a certain part of my job, it was a nice bonus. The focus was always ‘What can you do for the company?’ As a foreigner, the whole experience was interesting and intriguing, but definitely not fun.

What I really love about the Data School (at least so far in the training) is that they let and encourage you to do what you like and are good at. I’m surrounded by peers who also enjoy doing data analysis. These two factors mean a lot to me, not only because of my (not so fun) experience of working in Japan but also because I was feeling a little weary of doing data analysis/visualization alone by myself (FYI: COVID-19 delays our start date by 2 months).

No resume application process

I talked about this a lot, but I strongly feel the need to write about this. One of my favourite things about the Data School is its application process. Instead of submitting a CV, we have to submit a Tableau dashboard. After joining the DS, I love this application process even more, because that’s why we have such a diverse group of data schoolers. My cohort, DSAU6, has people from a range of different countries, different background ranging from data science to marketing, with an even mix of male and female. Even so, we are still a bit on the less diverse side as we all are a bit tech/digital in our background. Previous cohorts have had PhD, scientists, and accountants. Back in my days in Japan, my cohorts were Japanese, and were very likely to have a salaryman dad and a stay-at-home mom.

Flat and laid-back culture

Another thing I really love about the Data School (and MIP) is that the organization structure is pretty flat. The CEO is not god, and our coaches, Craig and Dave, are not only friendly and helpful but also welcome criticism about their teaching/training style. I also get to receive tons of feedback (good and bad) from my coaches, peers, and colleagues which I am super grateful. (Fun Fact: Japanese people don’t have a habit of giving feedbacks to just anyone. It’s a ‘special thing’ they only give out if they consider you to be ‘under their wings’.)

Last but not least, I really love how laid-back and casual the culture is. Unless we have a meeting with clients, usually we are allowed to wear whatever we want. Not only is it more comfortable, but it’s also nice to see a bit of everyone’s personality in their style. (Fun Fact: try wearing bright red in Tokyo’s train station at 9-ish in the morning. I bet everyone will throw you weird looks. Most people wear black suits there, it’s pretty gloomy.)





Amy Tran
Author: Amy Tran