How I got here

TODO — this draft is written from your own notes. Read it properly and make it sound like you before it goes anywhere near the live domain.

I wanted to work on AI long before I had any idea how. It stayed an interest rather than a plan, and when the time came to choose a degree I ended up in Computer Science almost by accident — which at the time felt like being sent in the wrong direction.

It was not. Computer Science turned out to be exactly the thing I needed first: algorithms, programming, mathematics, statistics, systems, and how computation actually behaves. Machine learning stopped looking like magic once those were underneath it.

What holds my attention now is not whether a model works but why it works. Optimisation, statistics, the behaviour of algorithms, deep learning, reinforcement learning, and the nature-inspired end of the field — genetic algorithms, ant colony optimisation, complex systems. The pleasure is in the moment a question moves from is this even possible to let me try it and see what happens, and then watching something behave more intelligently than the code you wrote would suggest.

What I do now

I work as a Data Scientist. Day to day that means building and maintaining data systems: pipelines, transformations, reporting that runs on its own, and the models and analysis that sit on top. Increasingly the interesting part is the engineering around the model rather than the model itself.

Where this is going

TODO — say what you are deliberately building toward, in one short paragraph. Let the projects prove it rather than the sentence.

Outside of this

Football, guitar, walking, photography, books, and a steady habit of taking on projects that are slightly larger than sensible.