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.