My mom is Japanese, my dad is Italian, and I was raised in Italy, where I completed high school before moving to the UK for university. In the UK, I earned a Master’s in Finance and started working in the financial data industry, including three years at Bloomberg.
Later, I moved to Japan, completed an MBA, and eventually joined Le Wagon Tokyo for their Data Science & AI bootcamp.
My journey has always been international, but the common thread has been finance and data.
I’m a Risk Manager at an asset management company in Japan. My job revolves around applying mathematical models to assess investment risk, monitoring portfolios, and explaining performance drivers to stakeholders.
My team handles data constantly by extracting, cleaning, processing it, and translating it into something decision-makers can act on.
Programming was always somewhere in the background but never central for me. I wrote scripts when necessary, automated basic tasks, tweaked inherited tools, and even worked with somewhat Java-based internal systems. Most of what I learned came from short courses, online materials, or figuring things out under pressure.
And over time, I realized that programming and data skills would continue to be in demand and would strengthen my long-term career prospects. That’s how I found out about Le Wagon Tokyo’s data science course.
I completed the program part-time while working full-time. Toward the end of the course, my workload increased significantly, and that made the final stretch particularly intense. If I could redo it, I’d give myself more breathing room.
The most memorable part of the bootcamp was the pair programming, and I found it extremely valuable. Sometimes I was the one relying on my partner to understand a concept, and other times the roles were reversed.
What stood out to me was how much teaching someone else deepens your own understanding. The bootcamp also helped me recognize that some of the knowledge I had before wasn’t as deep as I thought. And no – I definitely wasn’t the strongest student in the class (laughing)
As a risk manager, I apply mathematical models to assess how risky investments are. If something is losing money, I investigate why and what factors are driving the loss, what risks are materializing, and whether adjustments should be made. The goal is to turn data into insights that help key stakeholders make better decisions. That’s why I’d say the Data Science course really covers a core part of the job. It teaches you how to actually work with data in a practical way and how to use it to drive real business decisions.
We rely heavily on automation for our workflows, and while our solutions worked before, they weren’t always built with strong structure or testing in place. After the course, I started applying better coding practices and proper testing standards. Gradually, the quality of my codebase has improved: it’s cleaner, more reliable, and easier to maintain.
AI is definitely transforming finance.
I believe it will replace many tasks, especially repetitive or manual processes. But whether it replaces people depends on how individuals adapt.
Even if AI generates a functional piece of code, you still need to understand what it’s doing. If something breaks or produces unexpected results, you must be able to troubleshoot and adjust it.
I often compare AI to a high-performance car. You still need to know how to drive, and it just makes you faster and more efficient. Those who adapt and grow with the tools will remain valuable. Those who rely on them blindly may struggle.
Outside of work and technical upskilling, I spend a lot of time with Toastmasters, a public speaking organization. I organize events, coordinate members, and it has definitely improved my confidence and helped me collaborate with others.
And if we’re talking strictly about hobbies outside of professional development, then it’s… football!
Thanks a lot for the interview, Stefano! Good luck in your further milestones.
Data Science Full-Time (9 weeks)
April 6 to June 5, 2026
July 6 to September 4, 2026
Data Science Part-time (24 weeks)
March 28 to September 4, 2026
Data Analytics Part-time (24 weeks)
April 4 to September 4, 2026
In an effort to make the city more sustainable, Porto has begun to return public
After working as an advertising creative for 8 years in Australia, Tristan was on the
No-code tools are game-changers, enabling people to build applications and automate processes without extensive coding
In the digital era, the role of web developers is constantly evolving. With the advent
After studying languages, Annmarie worked several administration and communication roles. Feeling like there was more
At Le Wagon, we want to encourage women to follow in the footsteps of great
