Arthur Turrell is an Innovation Fellow and data science leader with a decade of experience at the intersection of economics, statistics and research, currently holding roles at 10 Downing Street, the Royal Statistical Society and the Bank of England. He combines a PhD in Physics and Part III Mathematics with hands-on econometric and data-science practice developed across the Office for National Statistics and central banks, translating complex quantitative problems into policy-ready insight. His work spans research management, financial-stability modelling and public-sector data innovation, and he authors practical teaching materials—such as the Coding for Economists quickstart notebook—to make coding accessible to economists. Notably, his background in high-energy physics gives him a rigorous, experimental approach to modelling and uncertainty that informs both technical and strategic decisions.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at Imperial College London
Master's Degree, Part III Mathematics, Master's Degree, Part III Mathematics at University of Cambridge
BSc, Natural Sciences (Mathematics and Physics), BSc, Natural Sciences (Mathematics and Physics) at University of Durham
This repository hosts the code behind the online book, Coding for Economists.
Role in this project:
Data Scientist
Contributions:3 releases, 4 reviews, 350 commits in 2 years
Contributions summary:Arthur contributed to the development of a quickstart tutorial for a book titled "Coding for Economists". The commits included adding example Python code, and explanatory markdown, including data exploration, analysis, and presentational techniques to give a taste of coding by covering a mini-project from end-to-end. The changes include the creation of a jupyter notebook to be launched on Google Colab.
Contributions:223 commits, 2 PRs, 315 pushes in 7 years 5 months
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