# 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

- **GitHub**: [areeslindley](https://github.com/areeslindley)
- **Email**: [alun.rees-lindley@outlook.com](mailto:alun.rees-lindley@outlook.com)
- **LinkedIn**: [alun-rees-lindley](https://www.linkedin.com/in/alun-rees-lindley/)

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