First Glimpse into Software Engineering @ Mobigen
Joined as a data analyst, but started to notice how engineers work and what it's like to build a real software product. It was also when my interest in Python—and machine learning—really took off.
It was my second job as a data analyst, but the first time I worked at a company that actually shipped software products.
Mobigen already had a few B2B SaaS offerings generating revenue when I joined, and their engineering department was sizable. I was part of a brand-new data analytics team they were forming. I didn’t get to work directly on the product codebases, but I sat near the engineering team, and it was hard not to be curious about how the whole system came together.
Python was their go-to language, and you could tell the engineering culture was strong—our CTO even ran a weekly Python study group for newcomers, which I joined. My background was in R, but being surrounded by Python-fluent engineers and data analysts, I naturally gravitated toward the Python data ecosystem: pandas, NumPy, scikit-learn, and matplotlib.
Around this time—2016 and 2017—interest in machine learning was exploding. Online lectures by people like Andrew Ng, Yann LeCun, and Christopher Bishop made these topics feel newly accessible. Everyone seemed to be talking about deep learning, TensorFlow, and the future of AI.
I was caught up in the excitement too, but what stuck with me more than the algorithms themselves was how software was built to serve real users. Although there weren’t many interactions, watching engineers at work gave me my first glimpse into software engineering—and planted a seed that would grow into something more.