PhD social statistician with 18 years’ experience helping public, private and third-sector organisations turn complex survey and administrative data into clear, usable findings.
I’m a quantitative researcher, data analyst and PhD social statistician with 18 years’ experience across research, data analysis, consultancy, financial analysis and R development.
Most of my work involves helping clients make sense of complex or messy data. I’ve worked with universities, charities, public sector organisations and private clients on projects involving survey design, data cleaning, statistical analysis, modelling, automated reporting, data visualisation and research writing.
I particularly enjoy projects where the challenge is not just running the analysis, but working out what the client actually needs from the data. I have a background in management consultancy as well as academic research, so I try to be practical: understand the objective, agree the best route, and produce outputs that are clear, robust and genuinely useful.
My academic work has been published in peer-reviewed journals and book chapters, and I have worked with organisations including the Alan Turing Institute, King’s College London, the University of St Andrews, the University of Manchester and the Runnymede Trust.
I work mainly in R, including automated workflows, R Markdown and Shiny, but I am equally comfortable producing clear Excel outputs, written reports, charts, tables and statistical summaries for non-technical audiences.
Outside work, I’m interested in music, electronics and making things, which probably explains why I enjoy building practical tools rather than just producing one-off analyses. My aim is to make data work easier, clearer and less painful for the people who need to use it.
Work Terms
I usually work on a project basis, with the scope agreed before work begins. For larger or less clearly defined projects, I am happy to start with a short scoping stage to review the data, understand the requirements, and agree the most sensible approach before committing to the full analysis.
My preferred communication style is clear and practical. I am happy to use platform messages or video calls where useful, but I generally prefer to keep key decisions and requirements written down so there is a clear record of what has been agreed.
For data analysis projects, I normally ask for the questionnaire, data dictionary or variable list, raw data files, any weighting or sampling information, and examples of the output format you want, if available. This helps avoid wasted time and makes the final output more useful.
I can provide outputs in a range of formats, including Excel workbooks, CSV files, Word documents, HTML reports, charts, tables, R scripts, R Markdown files or Shiny tools, depending on the project.
For fixed-price work, I prefer to agree milestones tied to clear deliverables, such as initial data review, draft outputs, final analysis, and final report or code delivery.