) · Practical understanding and hands-on experience with regression modelling (linear and logistic) · Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences · Direct experience with both supervised learning methods (linear and logistic regression, time-series modelling, generalized linear models, decision trees, random forests, support vector machines, etc