Interview No. 32: Daichi-san (Part 3) – Meaningful Work

“There are moments when data reveals the human stories behind it.”
Finding meaning in data analysis work

── Please tell us about your background.

Most of my experience with data was limited to academic settings. At university, I majored in Computer Science and Cognitive Science, and worked on coding assignments using languages such as Python, Java, and C/C++. I also studied data-processing technologies such as SQL, NumPy, and Pandas, and during a neuroscience research internship I handled tasks involving data manipulation. However, I had no prior experience applying these skills in an industrial setting.

──Please tell us about the work you were involved in.

I worked on analyzing and processing a company’s purchasing history data, extracting trends and information as required. After receiving instructions from the project manager regarding the output format, I would spend several days to a few weeks creating simulation data, checking its quality and clarifying uncertainties along the way. In my first project, I extracted items that had been purchased only once within the past one, two, or three years, and counted the number of such cases for each unique item number. I reviewed the output results in Excel and created functional specifications and data flow diagrams to document each step.

──What tools or systems did you use?

The main tools I used were Alteryx, Excel, and PowerPoint. Rather than introducing new systems, the focus was on organizing and analyzing existing data.

──What challenges did you face?

There were two major challenges. The first was the language barrier. While I grew up speaking both Japanese and English, my Japanese reading and writing ability eventually became (and remains) weaker compared to my English. The second was my unfamiliarity with Japanese engineering and business culture. I struggled with practices such as thorough documentation, detailed progress reporting, and strict role division.

──How did you address these challenges?

My colleagues were extremely kind and answered my questions on a wide range of topics, from vocabulary to project management to data systems. Whenever I was unsure about something important, I did my best to ask immediately, and when mistakes were pointed out, I took them as opportunities to learn. Through this process, I gradually overcame these difficulties.

──What aspects of the work did you find meaningful or interesting?

Through explanations from the project manager about why clients requested certain outputs and how those results would be used, I gained the experience of viewing data from a business perspective. I learned to approach tasks not just as producing correct outputs, but with an awareness of their usefulness to clients.

What struck me most was the various ways in which data can reflect human activities. For example, when analyzing items purchased only once, I learned that initial purchases involve extra steps such as paperwork and price negotiations, so reducing one-off purchases helps lessen the burden on staff. Knowing this background made me realize that rows of numbers directly represent workload and human actions. Data is not lifeless — it’s a record of choices and behaviors. By interpreting it, we can uncover a company’s challenges and areas for improvement. This was one of the most fascinating parts for me.

──In what ways did you feel you grew through this project

My Japanese reading and writing improved significantly. Improving my Japanese ability was one of the reasons I chose to work at a Japanese company while living in the U.S., so this was a major step forward. I also learned the importance of accurately understanding client requirements and avoiding confusion or unnecessary steps. Beyond logical correctness, I developed the habit of asking whether the result is actually useful.

── What was your impression of working at HumaneTech?

To be honest, the reason I chose HumaneTech was simply that I happened to be introduced to the job at the right time while I was job-hunting. What impressed me, however, was the “goal-oriented culture.” I found it to be an efficient, healthy workplace without wasteful practices. Even though my initial reason for joining wasn’t particularly strong, I am very satisfied with the outcome of working at HumaneTech.

──How would you rate your satisfaction (out of 5)?

Satisfaction: 5/5

My teammates were kind and offered fair, constructive feedback. I also enjoyed being entrusted with tasks that required creative problem-solving for logical issues.

──What kind of career do you hope to pursue in the future?

Through my work at HumaneTech and exposure to different tasks, I came to appreciate the appeal of data engineering and logical work. In particular, I became deeply interested in interpreting human behavior and decision-making through data.

At the same time, I’ve known for some time now that what I find most fulfilling is acting as a catalyst for others to gain new knowledge. This is a more human and meaningful role than simply handling data.

Hence, my current hope is to eventually become a clinical psychologist. I feel great purpose in facing individuals one-on-one and supporting their growth and transformation.

──What message would you give to future data engineers?

The key to success lies in communication with both colleagues and clients. If something is unclear, it is wise to ask questions without hesitation. At HumaneTech, I was never belittled for asking even basic questions. That’s why my advice is: “Don’t be afraid to ask.”