About Me
Data Analyst · London · Turning complexity into clarity
There's always a gap between the data an organisation holds and the decisions it actually makes well. I've spent my career trying to close that gap — through better pipelines, cleaner models, and dashboards that people actually open.
My work spans the full analytics stack: writing complex SQL to extract and model data, using Python for analysis and automation, and building Power BI dashboards that translate numbers into action. I care about the output being useful, not just technically correct.
Outside of work I've been building Hoodly — a personal project that scores 150+ London neighbourhoods across 20 factors, and a London Location Finder that uses Dijkstra's algorithm on the TfL network to find the best place to live given where multiple people need to commute. Both projects reflect what I care about: using data to answer questions that genuinely matter to people.
Get in touchBased in
London, UK 🇬🇧
Focus
Analytics engineering, business intelligence and advanced analytics — ideally work where data and commercial strategy sit close together.
Interests
Urban data, geospatial analysis, housing markets, transport networks, and making dashboards people actually want to use.
Technical Skills
A broad stack with depth where it counts — SQL and Python at the core, Power BI for delivery.
How I Work
🎯
Good analysis creates better decisions. I care as much about how findings land with stakeholders as I do about the methodology — the deliverable matters, but the outcome it drives matters more.
🔎
Before building anything, I ask whether the data is actually telling us what we think it is. Garbage in, garbage out — always.
🗣️
The most impressive thing a dashboard can do is make a complicated thing obvious. Simplicity is the skill.
🏗️
Pipelines, models and dashboards that don't break when the data changes. Maintainability is a feature.
Next Steps
Take a look at Hoodly and the London Location Finder in the projects section.