Neal is currently a Staff Machine Learning Engineer at Monzo Bank in London, where he focus on building machine learning systems to help make money work for everyone (reviewed in 2020, 2021, 2022) and Monzo’s machine learning platform.
:airplane: Before joining Monzo, Neal was a Senior Data Scientist at Skyscanner, where he built recommender and ranking systems to improve travel information in the app.
:school: / :calling: Before Skyscanner, Neal was a Senior Research Associate in the Computer Lab at the University of Cambridge, working on healthcare mobile apps that use smartphone sensors. He spun out this research into a startup that was part of Accelerate Cambridge in the Judge Business School.
:mortar_board: Neal did an MSci in Computer Science, PhD on recommmender systems, and first postdoctoral research position on urban data science in the Department of Computer Science at University College London, where he's still an Honorary Research Associate. While at UCL, Neal also spent time as a visiting researcher at Telefonica Research, Barcelona and worked as a Data Science consultant.
:bulb: Neal's work has always focused on systems that use machine learning - this has taken me from recommender systems to urban computing and travel information systems, digital health monitoring, smartphone sensors, banking, and open source machine learning tools. You can read more about Neal's work and research in the Press & Speaking
