About Me
Data Analyst · London · Turning complexity into clarity
I work across data analytics, engineering, and visualisation, primarily using SQL, Python, and Power BI.
My focus is on making data genuinely useful: building reliable pipelines, modelling complex datasets, and creating dashboards that support better decisions.
Outside of work, I'm building Hoodly, a data-driven platform that scores more than 150 London neighbourhoods across 20+ factors and includes tools like a London Location Finder that uses Dijkstra's algorithm on the TfL network to help people optimise where they live based on multiple commutes.
I enjoy projects where data can simplify complicated, real-world decisions.
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, but only if it actually lands. I put as much thought into how findings are communicated as into the work behind them.
🔎
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.