SA
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Areas of Consultancy: Applied operational researchBayesian methodsDesign and analysis of experimentsExpert systemsExploratory data analysisForecastingMultivariate analysisNon-parametric statisticsNumerical analysis and optimisationProbabilitySpatial statisticsStatistical computingStatistical inferenceTime series
Region of consultancy: Worldwide
Stephen is a Chartered Statistician and Chartered Mathematician who helps organisations turn complex data into robust, defensible and decision-ready models. His work spans pricing strategy, credit risk, forecasting and machine learning, with particular expertise in regulated environments where analytical models must withstand rigorous governance, validation and audit scrutiny. His applied experience covers healthcare, banking and commercial services. He has developed pricing algorithms and analytical frameworks that have improved margins and informed revenue decisions worth tens of millions, and currently leads data science work supporting large-scale pricing and strategy within the health insurance sector. Methodologically, Stephen works across Bayesian and non-parametric inference, stochastic modelling, optimisation, uncertainty quantification, including conformal prediction, and graph-based deep learning. He combines statistical rigour with strategic decision-making, complemented by executive strategy training. Beyond industry, Stephen serves on professional committees and national-level research and review panels. He sits on the editorial boards of several academic journals, reviews research for leading machine learning and AI venues, and teaches and supervises postgraduate research projects in machine learning, data science and quantitative methods, bridging advanced academic methods with real-world industry applications.
B.tech Applied Math; MRes Applied Computing: Fellow BCS, Chartered Statistician (RSS); Chartered Mathematician (IMA); Certified Mgt Consultant (IMC), Fellow IMC, Adv. Data Science Professional (AfDSP).