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Full-time
postgraduate degree
Posted 3d ago
Apply by Aug 25
~40 hrs/week
Responsibilities
Design, develop, validate, and optimize credit risk models across the customer credit lifecycle. Apply advanced statistical, machine learning, and AI techniques to generate business insights and improve risk decisioning.
Requirements
Requires a Master's degree in a quantitative discipline and strong expertise in credit risk measurement methodologies. Proficiency in Python, SQL, and Google Cloud Platform is essential, along with experience in PD, LGD, and EAD modelling.
Full job description
We are looking for a skilled Credit Risk Modeler to design, develop, validate, and optimise credit risk models across the customer credit lifecycle. The successful candidate will apply advanced statistical techniques, machine learning methodologies, and artificial intelligence solutions to generate actionable business insights and improve risk decisioning processes.
The ideal candidate will possess strong quantitative skills, experience in Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) modelling, and the ability to communicate complex analytical findings to both technical and business stakeholders.
Experience with cloud-based analytical platforms, particularly Google Cloud Platform (GCP), is highly desirable.
Related keywords
Credit Risk ModelerProbability of DefaultLoss Given DefaultExposure at DefaultMachine LearningArtificial IntelligenceGoogle Cloud PlatformPythonSQLSASRLinear RegressionLogistic RegressionANOVAANCOVADecision Trees
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