I look for the pattern before I reach for the tool.

Istudied physiology before I studied data, which meant I learned to ask “what's actually going on here” long before I learned to code. In the lab, a spike on a chart was never just a spike; it was a heart rate, a hormone, a body trying to hold itself in balance.

That instinct followed me into Python. Cleaning messy datasets, questioning what a gap in the data actually means, building small, focused tools that answer one question well, rather than dashboards that answer none in particular. The tool changed. The question didn't.

My degree was a Second Class Upper from Delta State University, Abraka, but the more useful thing it gave me was a way of thinking: look for the mechanism, respect the noise, and never trust a number you can't explain in a sentence.

Since then I've built five independent projects end-to-end: a content-based movie recommender using TF-IDF and cosine similarity, and exploratory analyses of Netflix, Spotify, breast-cancer diagnostics, and Nigerian adolescent fertility data. The clinical ones felt closest to home; my physiology background turned rows of cell measurements into something I could actually read.

I'm looking for my first role in data, ideally somewhere that treats analysis as a way of understanding people, not just decorating a report. Somewhere I can keep asking the question that started all of this.