Experience
Matthew has nearly 30 years of experience in the Mining Industry as a project and resource geologist and data scientist. Matthew’s expertise includes data wrangling, data analytics, data visualization, machine learning, statistical hypothesis testing, spatio-temporal modelling, simulations (Monte-Carlo and geostatistical), optimisation and survival analysis. Matthew is skilled at using the R language and environment for data analysis and for prototyping algorithms for automated data preparation and analytics. Matthew has applied data science to geology, hydrology, metallurgy, geometallurgy and equipment maintenance (survival analysis and Hidden Markov modelling). Generative and Discriminatory machine learning techniques that Matthew enjoys using include UMAP dimension reduction, K-means clustering, decision tree and random forest classification, Cubist and Gaussian Process regression, Neural Network autoencoders, and Bayesian Networks.