Nick Radcliffe
Nick Radcliffe is a practising data scientist with over 30 years experience, from neural networks (a.k.a. deep learning) and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007, he has run Edinburgh data science specialists Stochastic Solutions Limited.
Nick uses his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and was a key developer of Uplift Modelling—a method for modelling the differential effect of a treatment across a population.
Over recent years, he has developed a particular focus on testing data and data processes for correctness, developing and applying a methodology and set of tools known as test-driven data analysis (TDDA), with open-source and proprietary variants. These will feature in talks and training sessions in this year's DataFest.
Nick is also a Visiting Professor in the Department of Mathematics at the Edinburgh University and organises the PyData Edinburgh monthly meetup, which regularly brings together around 100 data scientists. He has acted as an adviser and consultant to various firms including SEP and Fluidinfo and has co-authored two books.
Sessions
Test-driven data analysis is a methodology and open-source Python library for improving quality in data processes. It covers three main areas:
• Testing data (generating constraints and using them to validate new data)