About Me

About Me#

Professional Background#

I’m a Statistical Methodologist at the UK Office for National Statistics (ONS), where I work on developing and applying statistical methods to produce high-quality official statistics. My role involves both methodological research and practical implementation, ensuring that statistical techniques are both theoretically sound and practically applicable.

Education#

PhD in Computational Physics — University of Warwick

My doctoral research focused on computational methods in physics, developing skills in numerical simulation, data analysis, and mathematical modeling that translate directly to data science applications.

Research Interests#

  • Statistical Methodology: Official-statistics methods, including survey estimation and small-area models (Fay–Herriot / EBLUP)

  • Machine Learning: Applied ML for classification, regression, and time series

  • Time Series Analysis: Seasonal adjustment, forecasting, and state-space modeling

  • Reproducible Research: Best practices for statistical computing and documentation

  • Sports Analytics: Applying statistical modelling to rugby union, rugby league, NFL, and cricket — including Elo rating systems and geospatial analysis

Publications & Writing#

  • Significance Magazine — Regular contributor covering sports analytics and applied statistics. Recent pieces include a Women’s Six Nations data analysis and a Super Bowl prediction model using NFL tracking data.

  • RSS Statistics in Sport — Committee member of the Royal Statistical Society’s Statistics in Sport section.

Skills & Expertise#

Technical Skills#

  • Programming: Python (pandas, scikit-learn, numpy, matplotlib, plotly, pymc), R (tidyverse, rjd3/JDemetra+, KFAS, xts, Shiny, R Markdown/Quarto)

  • Statistical Methods: Seasonal adjustment (X-13ARIMA-SEATS, TRAMO-SEATS), state-space modelling, small-area estimation (Fay–Herriot), regression, classification, time series analysis, Bayesian methods

  • Machine Learning: Supervised learning, ensemble methods, model interpretation

  • Data Visualization: Creating clear, informative visualizations for technical and non-technical audiences

Domain Expertise#

  • Official statistics production

  • Survey methodology

  • Seasonal adjustment techniques

  • Statistical quality assurance

Contact#

This portfolio represents my personal work and does not necessarily reflect the views or policies of the Office for National Statistics.

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