About Me

The story so far

I started my career working with accounting and finance software, where accuracy, attention to detail and problem-solving quickly became part of my day-to-day work.

As my experience grew, so did my responsibilities, evolving beyond software testing into reporting, dashboard development, data analysis and improving how information was presented and used.

Over the years I've worked closely with customers and internal teams to understand reporting requirements, investigate data issues and develop solutions that support better business decisions.

That experience taught me that successful analytics isn't just about producing accurate results. It's about understanding the business context, asking the right questions and presenting information in a way that helps people make confident decisions.

I'm currently completing the Cambridge University Career Accelerator, a Master's Level (Level 7), non-credit-bearing programme in Data Science, Machine Learning and Artificial Intelligence.

Through the programme I've built projects covering forecasting, neural networks, clustering, anomaly detection and machine learning, while continuing to build on the analytical thinking developed throughout my professional career.

My current focus is exploring how AI can enhance forecasting workflows. I'm particularly interested in combining time series forecasting, large language models and intelligent automation to improve SKU-level demand forecasting, inventory planning and business decision-making.

The aim is simple: use modern tools to make analytical work clearer, faster and more useful to the people making decisions.