Henry Wilde

Summary

I am a thoughtful, ethically minded scientist with a track record of pragmatism and efficient, impactful work. I have a breadth of projects under my belt from large-scale health data analysis with machine learning to productionising secure enclaves for record linkage. I find great joy in picking up new tools and techniques, and in putting those skills to use at pace.

Currently, I am leveraging LLMs to realise business efficiencies in the ONS, and I champion the increased use of privacy-enhancing technologies (PETs) across the Civil Service and Government.

Having successfully led numerous high-impact projects in academia and government, I am now looking to apply my expertise as a data scientist and software engineer in a new venture.

Employment

May 2022 - present Data scientist  Data Science Campus, Office for National Statistics

• Developing a LLM-based reader to summarise ONS activity in parliamentary debates, leading to significant cash savings for the Office
• Core developer of a privacy-preserving record linkage toolkit, including an accompanying secure computation architecture on GCP
• Mentored a team of apprentices in creating a Python interface to the England and Wales 2021 Census API
• Technical lead and project owner in creating high-fidelity synthetic census microdata using distributed computing and differential privacy

Python (data science stack, BeautifulSoup) | Version control (Git, GitLab, GitHub) | Google Cloud Platform | Docker | Automated testing (pytest, hypothesis, GitHub Actions) | Publishing (Quarto, Streamlit, GitHub Pages, Markdown, LaTeX) | LLMs (Gemini, OpenAI, LangChain) | Distributed computation (Dask, PySpark, Google BigQuery)

Feb 2021 - May 2022 Research associate  Water Research Institute, Cardiff University

• Designed and implemented the software infrastructure for the Welsh Government wastewater surveillance programme
• Taught myself the principles of R for data science in the first month to establish reproducible ETL pipelines for biochemical data
• Developed two core models for monitoring COVID-19 prevalence across Wales: a hierarchical GAM for predicting case rates and a Bayesian model to account for dilution in the wastewater system
• My analysis and reporting had a direct impact on Welsh Government policy at the height of the pandemic

R (tidyverse, mgcv, Shiny, RStan, RMarkdown) | Version control (Git, GitHub) | LIMS

2019-2020 Volunteer consultant  School of Biosciences, Cardiff University

• Commissioned by the largest school in the University to improve their dissertation allocation process
• Implemented a hands-off, programmatic framework using a Python research library I developed during my PhD
• Reduced the workload from a week across the team to a matter of seconds on one computer, and guaranteed mathematical fairness

Python | Version control (Git, GitHub) | Jupyter | Microsoft Excel

Dissertation supervisor  School of Mathematics, Cardiff University

• Co-supervisor for a MMORS final-year project on Folk Theorems in game theory
• Mentored the student in how to produce a sustainable piece of research software to accompany their dissertation
• Assisted in editing the final report prior to submission

Python | Version control (Git, GitHub) | SQL | LaTeX

2017-2021 PhD studentship teaching  School of Mathematics, Cardiff University

• Heavily involved in teaching modules and services, including courses on statistical inference and Python for mathematics, the university maths support service, and hackathons for Masters students
• Founded an Advanced Python Workshop for my fellow PhD students covering topics like distributed computing, automated testing, and version control
• Mentored a high school student during a Nuffield Research Placement

Python (data science stack, SymPy, Dask) | Version control (Git, GitHub) | Testing (pytest, hypothesis, Travis CI) | Writing (LaTeX, Markdown, reStructuredText, Sphinx)

Education

2017-2021 PhD Applied Statistics, Operational Research and Data Analytics  School of Mathematics, Cardiff University

• My thesis focuses on the thorough and ethical utilisation of machine learning in healthcare settings
• Key results include new perspectives on algorithm evaluation through data synthesis, and fair clustering
• My research provided actionable insights for my co-funders into a critical healthcare population in their care using only administrative data
• Accompanied by a suite of sustainably developed research software packages

2014-2017 BSc Mathematics (First Class Honours)  School of Mathematics, Cardiff University

• Maintained a breadth of interests, including operational research, computing, and pure mathematics
• Received perfect scores for two projects: a simulation and analysis of a hospital emergency department, and an empirical comparison of two strategies in an iterated Prisoner’s Dilemma

Awards

2022-2024 Reward and Recognition  Office for National Statistics

• Received a total of eight awards across all three bands, rewarding me for going above and beyond in my work
• Two awards for giving particularly accessible and engaging technical talks to colleagues in the Office
• Three awards for my involvement in high-priority surge work between governmental departments and with our international partners
• A sustained excellence award for my work on synthetic data and its impact on the ONS Data Strategy
• Two awards for fostering a culture in my teams that values software sustainability and effective project management practices

2022 PETs Hackathon  United Nations PET Lab

• Finished third out of two hundred international teams
• The hackathon was centred around a real-world application of privacy-enhanced data analysis
• Accurately predicted three hidden characteristics of Kenyan refugee households using open-source tools for differential privacy inside a secure enclave

2018 Support for NATCOR Bursary  Association of European Operational Research Societies

• Received financial support to attend postgraduate courses in operational research
• Courses covered approximation algorithms and heuristics, and predictive analysis and forecasting

Publications

A list is also available online.

Thesis

2021 Wilde, H. New methods for algorithm evaluation and cluster initialisation with applications to healthcare. Cardiff University. PDF. GitHub repository.

Journals

2022 Wilde, H., et al. Accounting for dilution of SARS-CoV-2 in wastewater samples using physico-chemical markers. Water, 14(18):2885. DOI:10.3390/w14182885

2020 Wilde, H., Knight, V. and Gillard, J. Evolutionary dataset optimisation: learning algorithm quality through evolution. Applied Intelligence, 50:1172-1191. DOI:10.1007/s10489-019-01592-4

Wilde, H., Knight, V. and Gillard, J. Matching: a Python library for solving matching games. Journal of Open Source Software, 5(48):2169. DOI:10.21105/joss.02169

Pre-prints

2024 Jones, O., et al. Estimating wastewater dilution using chemical markers and incomplete flow measurements: application to normalisation of SARS-CoV-2 measurements. DOI:10.20944/preprints202402.1109.v1

2022 Houssiau, F., et al. A framework for auditable synthetic data generation. arXiv:2211.11540

Interests

Cooking

I taught myself to cook as a child, and then worked as a chef while at sixth form, including at a former Michelin star restaurant. Cooking for friends and family is now one of my dearest pastimes.

Cycling

During the height of the COVID-19 pandemic, I desperately needed something to occupy myself outside of writing my thesis. So, I taught myself bike mechanics and renovated a vintage steel-frame touring bike.

D & D

I adore fantasy in all its forms. Now, after years of listening to Dungeons & Dragons podcasts, I serve as the game master in a homebrew campaign for my three brothers.