I am a data botherer. 

What I do is analyse data using whatever approach fits best. Actually, that’s not quite correct. I mostly attend meetings and write recommendation letters these days (I’m getting pretty good at both). But occasionally I carve out enough time to do some actual work and I’m never happier.

I paddle my metaphorical canoe at the confluence of clinical trials, medical statistics, causal inference, reproducibility and data science. The waters are choppy. And murky. And filled with hungry giant octopuses. Where was I?

I apply myself to human health- mostly physical activity and mental health but I increasingly work on policy evaluation.

I suppose the perfect study for me would be an open and pre-registered policy evaluation of physical activity on some health outcome (with free coffee, international travel and academic acclaim assured).

I am interested in bringing the rigour, methodology and philosophy of clinical trials into settings outside of trials, as well as delivering the insights that causal inference brings into the trials setting. If this sounds good to you, do get in touch.

I’m on LinkedIn, BlueSky and Mastodon

And for the search engine optimisation, here’s a word-explosion: statistics, causality, data science, machine learning, clinical trials, policy evaluation, Nobel-prize winning potential, devastatingly handsome, hilarious, genius god-like brilliance.