▎ Subject builds and scales data platforms, turning regulatory and scientific data into products, insights and decision-making capability. Trained as an astrophysicist; redeployed to capital markets.
Postings
London Reporting House // Chief Data Officer
Dec 2022 — present
Subject joined as the first data hire, when the company was pre-infrastructure and
pre-product, and advanced through Senior Analyst (2023), Head of Data & Analytics
(2025) into the Chief Data Officer post (2026).
London Reporting House builds cloud-native
data products, turning raw regulatory reporting into capital-market intelligence.
Office for National Statistics // Statistical Analyst
Oct 2016 — Sep 2017
Subject worked in Survey Methodology, on the processing, editing and imputation of
business survey data.
The ONS is the UK’s national statistical institute,
producing the official measures of the economy, population and society.
Cardiff University // Graduate Researcher
Jul 2016 — Oct 2016
Subject investigated stray light pollution around candidate target systems and wrote
a technical report for the European Space Agency.
ARIEL is an ESA mission to survey the atmospheres of
planets beyond the solar system.
Academic record
Imperial College London // PhD, Astrophysics
Oct 2017 — Aug 2022
Subject studied stellar variability, submitting a thesis on its simulation and
building actress, an open-source tool for modelling multi-wavelength light
variations.
Published work indexed on NASA ADS.
Cardiff University // MPhys, Physics
Sep 2012 — Jul 2016 · 1st Class Hons
Subject built SpotSim, a module for the
ExoSim end-to-end
simulator, modelling the stellar noise that starspots introduce into exoplanet
observations for transit spectroscopy surveys.
Twinkle is a British space mission to survey
faraway worlds.
Capabilities
Data engineering // PySpark, Airflow, AWS (S3, Glue, Lambda, Athena), Parquet
and Iceberg lakes, Postgres, Terraform, Docker, CI/CD.
Analytics & modelling // fact and dimension models, slowly changing history
(SCD Type 2), as-was versus as-is restatement, serving layers behind product APIs
and BI dashboards.
Machine learning // applied in research and in production: simulation and
satellite data, missing-data imputation, inference for data quality.
LLM & agents // skills, workflows and routines built on Claude Code,
integrated through MCP.
Data governance // pseudonymisation, statistical disclosure control, retention
limits and field-level treatment policy.
Applied cryptography // authenticated encryption, one-way hashing, key
management and zero-knowledge principles.
Languages // Python, SQL, Bash, Go, TypeScript, HCL