I am one of the founders of Bodywork Machine Learning, where I focus on developing open-source tools and best-practices for ML engineers. We help ML teams to bridge the gap between research-led (proof-of-concept) solutions and fully-operational ML systems, creating a path to production that is fast, reliable and repeatable. Our key technology is bodywork-core, which is used to deploy jobs, services and pipelines, without requiring engineers to get involved in containerisation, orchestration and infrastructure.
I have a background helping companies develop solutions to their data engineering and machine learning problems. I was Chief Data Officer for LiveMore Capital, where I built a data platform to support their credit analytics and modelling activities; I worked with Oracle’s AI Apps team, automating workflows for training, deploying and monitoring ML models embedded throughout Oracle’s cloud apps; and prior to all this I worked for Nova Fori, a FinTech scale-up and provider of B2B transactional platforms, where I was responsible for the research and development of trading algorithms and ML systems that enabled clients to derive value from trade-event data.
Before moving into the world of data science and machine learning I spent several years working as a quantitative analyst within London’s financial services sector. I specialised in pricing and modelling the credit risk on derivative trades. So I know a thing or two about stochastic processes, time-series data, Monte Carlo methods and financial mathematics.
Going back even further, I graduated from UCL with a PhD in Computational Neuroscience, that explored how machine-vision techniques can be used to better understand human visual cognition. I learnt a lot about statistical learning and neural networks - before any of this stuff was as powerful and popular as it is today. I also have a background in theoretical physics.
I am a competent software engineer, comfortable working with cloud-based distributed systems and I have had operational responsibility for many production services. I prefer to be hands-on, but I have also led cross-functional teams and managed technical projects from inception to delivery.