I am a freelance chartered statistician based in Hampshire, UK. Since 2017, I have been providing training, coaching and consultancy. My expertise focuses on Bayesian statistical models, evidence synthesis, data visualisation, health service evaluation, and communication to policy makers.
My clients have included the Cabinet Office, Harvard Medical School, the World Bank, The Economist, and the Royal College of Paediatrics and Child Health. I am also a zero-hours Senior Lecturer on Kingston University's MSc course in Data Science every Autumn.
You can read some vignettes of the freelance work I have done here. You will find my contact details via the menu above. Please note I have no availability for new freelance work.
My first book, "Data Visualization: charts, maps and interactive graphics" was published by CRC Press and the American Statistical Society in 2019.
The next is "Bayesian Meta-Analysis: a practical introduction", co-written with Professor Gian Luca di Tanna, scheduled to be published by CRC Press in June 2025. We are launching an online forum and blog, "the Bayesian Meta-Analysis Network" at bayesian-ma.net, which will start to be populated in November 2024.
I programmed the StataStan interface to Stan software for Bayesian inference, and the kudzu package in R and Stata.
I use a wide range of analytical methods: Bayesian, frequentist, likelihood and machine learning. I think that the right tool should be used for each job. My personal philosophical standpoint, which emphasises justified eclecticism, is here.
A list of publications — peer-reviewed papers, commissioned articles, posters, talks, reports — is available via the link above.
I started my company, BayesCamp, in 2017. Prior to that, I worked on:
I was a member of the Royal Statistical Society's statistical computing committee, and NHS England's National Advisory Group for Clinical Audit and Confidential Enquiries.
Degrees: BSc mathematical sciences (first class honours), diploma in statistics, MSc in medical statistics, PhD "Applications of Bayesian latent variable models to challenges in health and social care data".