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Commonwealth Bank is seeking an Advanced Analytics Analyst to build statistical and machine learning models for credit risk and commercial lending in Sydney. You’ll work within a small, experienced team to explore data, test methodologies and translate findings into real business outcomes.
You don't need to be a credit risk expert initially; strong quantitative foundations and willingness to learn are valued as you develop modelling capability and collaborate across lending domains, property
Our Credit Modelling team builds models, analytical tools and insights that help us make better lending decisions for our Business Banking customers.
We work on complex problems where the answer isn't always obvious. Rather than simply maintaining established models, we explore different data, methodologies and modelling approaches to understand a business problem and determine the right analytical solution. Our work spans areas including lending origination, servicing assessments, early warning and arrears, property analytics and the use of merchant data. We're a small, experienced team working on strategically important initiatives, and we're looking for an Advanced Analytics Analyst who is curious about data, enjoys solving problems and wants to develop their modelling capability in a supportive environment.
You don't need to arrive as a credit risk expert. We're much more interested in your quantitative foundations, how you think about data and problems, and your willingness to learn.
In this role, you'll support the development and management of statistical and machine learning models that help us understand risk and make better decisions for our customers and business.
You'll have the opportunity to:
The team supports model implementation and works closely with the areas responsible for deployment, but does not own model deployment itself.
We're open to different backgrounds. You may already work in analytics or machine learning, or you may be earlier in your career with strong quantitative foundations and practical analytical experience. We're looking for:
Experience in credit risk modelling would be valuable, but it isn’t essential. We welcome people from areas such as statistics, econometrics, mathematics, machine learning, customer analytics or other quantitative disciplines who are interested in applying those skills to credit and commercial lending problems.
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