Projects

Personal Project

Hoodly — London Neighbourhood Intelligence

A personal tool for finding the best London neighbourhood to live in — balancing commute requirements against the lifestyle factors that matter most to you.

Personal Project

London Pub Quiz Finder

A platform connecting pub quiz lovers and hosts across London — find, filter and book quizzes by location, date and team size, with live booking confirmations and team chat.

A Bayesian statistical model predicting the outcome of every English football match across multiple seasons — built on in-game stats and self-engineered features like rolling form scores.

Automated analysis of IKEA customer feedback across two international markets — replacing a slow manual review process with weekly product insights at scale.

Predicted which supporters were most likely to respond to each fundraising campaign, enabling smarter targeting and driving measurable uplift in response rates and revenue.

A cascading prediction model that gives customers an instant repair cost window at the point of booking — deployed as a REST API with progressive fallback logic for rare vehicle and job combinations.

Combined sales, demographic and migration data to rank geographic areas by revenue opportunity — giving an international client a data-driven view of where to focus growth efforts.

A configurable notification pipeline — designed once, deployed across multiple international client accounts — handling trigger logic, templating and delivery via API integrations.

Annual analysis of fundraising campaign performance — measuring spend efficiency, donor response rates and revenue attribution to directly inform KPI frameworks and budget allocation.

A demand forecasting model predicting customer fuel and energy order volumes for Certas Energy — improving planning accuracy and reducing the operational cost of reactive fulfilment.

Data engineering and cost analysis across Toyota Europe and North America — consolidating disparate source systems via ETL pipelines and surfacing operational efficiency opportunities.