Partner with the product team to determine how technology help to detect and reduce risk;
Analyze key metrics to determine risk;
Maintain the credit model platform which is utilised by the team and expected to provide advice and guidance on ongoing efficiency gains and new credit modelling methodology.
Have an undergraduate degree in an analytical discipline (e.g. maths, statistics), however other disciplines will be considered;
Have 5+ experience of working in credit / risk modelling for retail customers especially unsecured lending in bank or non bank;
Have significant experience of credit modelling using statistic tool such as R, Phyton SAS, SQL analytical tools or advanced MS Excel skills;
Previous experience building unsecured lending credit risk modelling is highly prefered.