Data Analyst with over 10 years' experience transforming business data into meaningful insight. Currently expanding my expertise in forecasting, machine learning and applied AI through the Cambridge University Career Accelerator.
I focus on practical analytics: understanding the problem, building reliable outputs, and turning data into something people can confidently use.
Turning complex business data into clear, actionable insight through reporting, visualisation and analysis.
Building forecasting models that help organisations understand demand, improve planning and make better decisions.
Exploring machine learning and AI techniques that enhance analytical workflows and solve real business problems.
A couple of projects that show how I approach applied AI and forecasting work — what each one does is explained on its own tile below.
An interactive, hosted demo of a real acquisition-screening tool — search a company, reconcile its accounts and open a deep dive, using real UK Companies House data.
Compared ARIMA, SARIMA, XGBoost, LSTM and hybrid models to forecast book demand and evaluate which approaches delivered the most useful business insight.
My background is in financial systems, reporting and data quality. That experience has shaped how I approach analytics: practical, detailed and focused on helping people make better decisions.
I'm currently developing my technical toolkit through the Cambridge University Career Accelerator, with a focus on forecasting, machine learning and applied AI.
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