Former economist, retrained in AI. Applying my numerical skills from economics to coding unleashed an insatiable curiosity for machine learning. I’m passionate about using machine learning to innovate large-scale NLP systems that can help founders make their mark in the global economy… as well as playing the violin!
Following my MSc in Economics at London School of Economics and Political Science, I worked as an Economic Consultant at Frontier Economics in London, Spain and Germany for four years. I worked with the European Investment Bank, Deutsche Telekom and the London Stock Exchange. Working a lot in econometrics, I ventured out into related fields like machine learning and programming for fun. Over the years I became more and more intrigued by machine learning, and realised that if I enjoy it that much, I should probably do it full time. So I went back to school again! This time for an MSc in Machine Learning at University College London, where I left with a Distinction and a spot on the Dean’s List 2016-17. Using my newfound knowledge, I headed to AI startup Kortical and worked as a Machine Learning Engineer for three years. Here I helped build a machine learning SaaS product with a heavy focus on Natural Language Processing. Then I made the exciting jump to one of London’s leading machine learning startups, Benevolent AI, again focusing on NLP, but applying it to biomedical text. There I built cutting-edge NLP models for finding and disambiguating different biological entities like diseases and proteins. I feel very lucky at Moonfire to be able to combine my fascination with quantum computing, web3 and my love for economics and machine learning (not least because Moonfire deals with a lot of NLP data!). I hope to use this combination to illuminate underrepresented founders. We’ve got your back.