Originally from France, Axel studied marketing and business with an international focus, earning a Master’s degree in International Marketing. He began his career in pharmaceutical market research, an industry he’s now been part of for over a decade.
After moving to Japan, Axel joined one of the world’s largest pharmaceutical companies. His role initially focused on classic market research, but over time it became increasingly analytics-driven.
“I understood the business very well,” Axel explains, “but I didn’t have the technical tools to go further.”
Things like SQL, Python, analytics workflows were becoming essential, but they weren’t part of his skill set yet. Axel wanted to understand how things worked, collaborate better with data engineering teams, and move faster.
Before joining the Data Analytics bootcamp in Tokyo, Axel was already using no-code tools internally and getting solid results. But there was a catch: learning on his own always came second to urgent work tasks.
“I did make some progress,” he says, “but only when I had time – and there was always something more urgent.”
What the bootcamp offered instead was structure and commitment: a defined timeframe where learning had to be the priority, even if it meant putting other things on hold for a few months.
Coming from a completely non-technical background, Axel joined the program with a clear goal not to replace engineers, but to understand automation, data pipelines, and code well enough to use them wisely.
“I work with people who are experts in coding. If I understand what they do, I can work with them much more effectively.”
Axel made his case to his manager and asked his company to fund the training.
His argument was simple: his role was evolving, and without new skills, he couldn’t work efficiently within normal hours. Investing in training would help him deliver better results for himself and for the company.
The company agreed and fully funded the bootcamp.
Right after finishing the program, Axel went on paternity leave to welcome his newborn son. When he returned to work, he remained in the same role but started actively applying what he learned, like Power BI for dashboards, SQL to read and understand queries, Python for analysis and automation and no-code tools.
“Before the Data Analytics bootcamp, I would read SQL queries and completely misunderstand them,” he says. “Now, I can generally understand what a query does. If it gets complex, I might ask Copilot but at least I know what I’m looking at.”
That confidence extends to AI tools as well. Axel now knows when Copilot’s output makes sense, and when it doesn’t.
In his day-to-day work, Axel sits right at the intersection of marketing, data science, and data engineering. Sometimes he handles analysis or dashboards himself. Other times, he translates business needs for more technical teammates and helps ensure the right solution is built.
He’s become a business-savvy analytics bridge.
Thanks a lot for the interview, Axel! Wishing you all the best in your career and family life!
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