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