Career Journey

My professional journey in data science, statistical methodology, and research.

Experience

March 2025 – Present

Senior Statistical Methodologist (SEO)

Office for National Statistics

Time series and seasonal-adjustment methodology for National Accounts. Act as interim G7 Lead, managing work allocation for a team of three and providing methodological consultancy to Bank of England and Treasury analysts.

  • Architected the migration of legacy economic modelling code to a modular R/GitHub RAP covering around 200 economic series, with full auditability for National Accounts (GDP, Retail Sales)
  • Developed automated diagnostic software and Bayesian state-space models for structural breaks in COVID-impacted tourism data
  • Seasonal adjustment and time-series production for high-profile published outputs
Technologies used
  • R
  • Python
  • X13-ARIMA
  • Git
October 2022 – March 2025

Senior Data Scientist (SEO) / Data Scientist (HEO)

Government Office for Science

Data science for science-and-technology insight and briefing. Promoted from HEO Data Scientist to SEO Senior Data Scientist.

  • Engineered a parallelised, agentic RAG tool using LangChain and the Claude API to automate legislative drafting — 3rd place, national AI hackathon
  • Migrated API extractions to Google BigQuery, increasing data granularity and reliability for Prime Minister briefings
  • Built spaCy/NLTK pipelines for automated horizon scanning of emerging technologies, supporting the UK’s Horizon Europe membership strategy
  • Line-managed HEO staff and oversaw departmental Azure cloud migration projects
Technologies used
  • Python
  • LangChain
  • BigQuery
  • Azure
  • Git
September 2018 – September 2022

PhD Researcher

University of Warwick

Computational plasma physics and inertial confinement fusion. High-performance simulation and numerical modelling.

  • Developed high-performance computational features for 2D hydrodynamics code (FORTRAN) and managed simulations on HPC clusters
  • Engineered a sports prediction engine using neural networks and gradient boosting
April 2018 – September 2018

Graduate Data Scientist

Admiral Group

First industry data science role, focused on fraud detection and actuarial pricing models.

  • Developed an imbalanced-class fraud detection model using R and SQL for suspicious claims
  • Reconstructed actuarial pricing models to improve risk-stratification logic and model explainability

Education

  • PhD in Physics (Fusion Energy — Computational) — University of Warwick, 2022
  • MSc Fusion Energy — University of York, 2018 (First Class Honours)
  • MPhys Physics — Durham University, 2016 (Upper Second Class Honours)

Certifications

  • AgilePM Foundation (APMG)
  • ONS Data Science Residency
  • Royal Statistical Society — Statistics in Sport Committee member; contributor to Significance