David Randell
Statistical Consultant
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolDavid Randell is an applied statistician with 8+ years’ experience advising industry and academia, currently a Statistical Consultant in Shell’s Statistics and Data Science group and a former Visiting Fellow at Durham University. He specializes in extreme value analysis and Bayesian methods, with a strong publication record on non-stationary extremes, spatial return levels, and variance learning for large-scale physical systems. His work blends practical industrial problem-solving—such as locating gas emissions and smart-well flow monitoring—with methodological advances in multidimensional covariate modelling. Based in Amsterdam, he brings deep domain expertise in ocean and storm extremes alongside hands-on experience deploying statistical models in engineering settings. Less obvious: his PhD research in Bayes linear variance learning underpins many of his applied approaches to inspection planning and uncertainty quantification.
8 years of coding experience
PhD, Bayes Linear Variance Learning for Mixed Linear Temporal Models, PhD, Bayes Linear Variance Learning for Mixed Linear Temporal Models at Durham University
Github Skills (9)
bayesian8
localization8
monte-carlo8
markov-chain8
python7
monitoring7
mcmc6
simulation3
computational-fluid-dynamics2
Programming languages (3)
Github contributions (5)
ECSADES/ecsades-matlab
Jan 2019 - Oct 2019
Contributions:7 commits, 7 pushes in 9 months
davidrandell84/pyELQ
Mar 2026 - May 2026
Contributions:3 pushes in 2 months
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