Consultants Directory


We provide a Directory of Statistical Consultants listing our professionally qualified members who offer a statistical consultancy service. Professionally qualified members hold the status of Chartered Statistician (CStat).

The Directory contains profiles created by the consultants, including information on their specialisms and background as well as their contact details. It operates on an opt-in basis – each consultant has agreed to their profile being available on our public website. There are terms of reference covering the operation of the directory, to ensure it remains up to date.

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Chris Naylor Expert systems; Bayesian inferencing using the XMaster expert system shell. Worldwide

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Dr. Joseph Yose Chartered Statistician and applied mathematician with expertise in industrial statistics, machine learning, process improvement, and Six Sigma methodologies. Currently serving as a Senior Analytics Consultant at Minitab, delivering statistical training and consultancy across manufacturing, R&D, and service sectors. Worldwide
Gabriella Debreczeni People Analytics (Business, Education, Healthcare, other public services). Regression analysis, survival methods in people data. Statistical programming in R. General statistical consulting. Worldwide

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Sara Hilditch
Jackie Campbell Applied statistics/data analysis Research design Commissioned research and evaluation Worldwide
Faisal Khamis Applied Multivariate Statistics, Applied Social Statistics, Econometrics, Mortality, Epidemiology, Biostatistics, Spatial and Temporal Statistics, Time Series Analysis and Forecasting, Regression Analysis, Structural Equations Modeling. Worldwide
Min Sun Data science in general, including but not limited to - Statistical modelling on multivariate and infinite dimensional variables with dimensional reduction, e.g. functional data analysis, GLM, mixed effect model, LASSO, Bayesian inference, survival analysis, circular statistics - Power/sample size calculation - Simulation - Statistical computing - Machine learning and deep learning, e.g. classification, clustering and image analysis - Non-parametric statistics - Applied operational research - System of differential equations - Graph theory & abstract algebra with applications to data analysis - Optimisation, with custom loss function Worldwide

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Shu Lee Data Science and Machine Learning
Dr Ian Hunt Statistics and probability reasoning for forensic science, expert witness statements/expert evidence (criminal and civil law), agri-food experiments, medical trials and investment finance analysis. Worldwide
Novri Suhermi Time Series Forecasting, Statistical Computing, R & Python Programming, Marketing Analytics Worldwide
Prof. Barry Quinn Open science analytics, Cloud computing and financial technology, Financial data science, statistical forecasting, machine learning and predictive analytics. Europe
Richard Saldanha Quantitative finance; AI/machine learning; mathematics/statistics. Worldwide

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Giovanni Montana Machine learning, computer vision, medical imaging, deep reinforcement learning Worldwide

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Char Leung

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John Henstridge

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Mark Strong
Jason West Bayesian analysis. Statistical methods. Epidemiology. Data science. Worldwide
Jo Morrison I am a consultant with the team at Select Statistics. We work in partnership with our clients providing independent statistical advice, support and analysis. Our clients range from large companies to individual researchers, working in a wide variety of fields. See our website for more details. I have over 20 years’ experience working as a statistician in education research. My experience includes analysing government and international datasets, linear regression and multilevel (mixed effects) modelling, item analysis and IRT, age-standardisation, sample size calculations, analysis of RCTs, survey design, analysis of surveys and factor analysis. A key part of the consultancy role is communicating results of complex analyses in accessible ways to non-statisticians. Worldwide

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Blaise F Egan Exploratory data analysis; Data visualisation; Forecasting and time series; Samples and surveys; Generalised linear models, Generalised additive models; Bayesian statistics;

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Adam Smith