HOW I GOT HERE — CURIOSITY BECAME A CAREER
I didn't choose data science because I'd always dreamed of working in AI. During engineering we had to pick a specialization, and data science was simply the one that intrigued me most — it wasn't a career plan, it was curiosity about something I knew very little about.
Then something unexpected happened. Studying statistics and machine learning, I realized what fascinated me wasn't building models — it was asking questions and uncovering answers hidden in data. I enjoyed the investigation as much as the result.
That curiosity turned into projects. My final-year Digital Twin asked what sensor data could tell us before a motor fails. During the IPL season I built a simulator and watched it correctly identify the eventual champion. Then I turned the question on something personal — could data explain why I keep making the same mistakes in chess? That became ChessIQ: 4,635 of my own games, honestly analyzed (it's also where I caught my own model cheating, walked it back from a flattering 78% to an honest 72%, and published the smaller number).
Whether it's catching a faulty government sensor in CivicLens or mapping careers in PsyMetric, the part I enjoy most isn't chasing accuracy — it's understanding real-world data and building systems that produce insights people can actually trust. I didn't fall in love with data science because of algorithms. I stayed because it constantly rewards curiosity: every dataset tells a story, every anomaly has a reason, and every project teaches me to ask better questions than the last.
