Skills highlighted in blue are preferred key skills
Bring practical python, sql, statistics and machine-learning capability. Solve business problems using predictive modelling and advanced analytics. Compare algorithms using suitable validation and performance measures. Work across forecasting, classification, regression, segmentation or nlp use cases. Explain model assumptions, limitations and business implications clearly. Partner with data engineers to obtain reliable production features. Monitor model quality and investigate drift or unexpected behaviour.
Opportunity for a ML Solutions Engineer to contribute to a growing technology, analytics, enterprise applications, or sales function.
Client Company