I am a freelance data scientist and engineer specialising in real-world data products and applied machine learning systems.
Previously, I led engineering at Octopus Energy's research lab, Centre for Net Zero. We simulated over 9 million households to find out whether the UK government will achieve its heat pump installation targets. I also used machine learning to predict household electricity consumption, so that network operators can target investment.
I have six years experience building products in fintech startups. At Fluidly (acquired by OakNorth Bank in 2022), I forecasted the cash flow of tens of thousands of small businesses. At DueDil, a company information platform, I worked for clients on bespoke data projects and built a system to identify companies in datasets without unique identifiers.
I have a PhD in Chemistry from Imperial College London, where I built chemical reactors to make high-quality nanoparticles for solar photovoltaics. My work has over 400 citations.
I deliver data science and engineering projects. My work includes:
- Turning prototypes into operational systems (MLOps)
- Design and build of cloud data warehouses
- Development of prototypes to validate solutions to business problems or exploit opportunities
- Improving the reliability and performance of legacy models and applications
- Exploration, analysis and visualisation of datasets
I can work solo or with your current team on projects up to 12 weeks long.
If you have an idea or project in mind, I’d love to hear from you: [email protected]