Quantitative Analyst, Non-Retail Models

· Apply quantitative modelling and analytics to support non-retail credit risk decisions across the Group.

· Join a collaborative Risk Management team where your work will help protect customers, strengthen the bank and enable sustainable growth.

· Use data, statistical techniques and emerging AI tools to develop innovative credit risk models and generate practical insights for our business.

Bring your ambition and we’ll help you grow, belong and shape what’s next in credit risk modelling and advanced analytics.

Do work that matters

Risk Management partners across the Group to identify, assess and manage risk, protecting our customers, strengthening the bank and enabling sustainable growth. You’ll join a collaborative team where you’ll solve complex challenges, influence better decisions, and use data, insights and innovation to make a meaningful impact.

As a Quantitative Analyst, Non-Retail Credit Risk Models, you’ll contribute to the development and enhancement of key non-retail credit risk models and methodologies across CBA. These models support important regulatory capital and collective provisioning requirements across CBA lending business units.

See yourself in our team

The Model Development Chapter Area sits within Risk Management and is responsible for developing credit risk models and performing advanced analytics across the Group.

In this role, you will:

· Build statistical models and perform analysis across CBA credit portfolios using techniques such as predictive modelling, non-linear regression, time series analysis, and macroeconomic modelling.

· Work with complex internal data sets, including imperfect or incomplete data, and help identify practical ways to address data challenges.

· Use tools such as R, Python, SQL, Teradata and AWS-related platforms to prepare, transform and analyse data for modelling purposes.

· Analyse the impact of our models into CBA’s key business metrics, including Expected Loss, Capital and Risk Weighted Assets.

· Clearly document modelling results, methodology choices, assumptions and conclusions so that stakeholders can understand, review and validate the work.

· Engage with model users, independent model validation, business unit risk teams and enterprise services teams across the modelling lifecycle.

· Explore how AI tools can be used thoughtfully to improve quality, efficiency, learning and insight generation, while maintaining accountability for final outputs.

We’re interested in hearing from people who:

We know great candidates may not meet every requirement listed below. If you’re excited about this opportunity and believe your experience could add value, we’d love to hear from you.

You will bring experience in several of the following:

· Quantitative statistical modelling, with strong problem-solving skills across modelling and data challenges.

· Credit risk modelling experience, ideally including PD, LGD or EAD models and exposure to non-retail portfolios.

· Strong capability using R or Python, with SQL experience and familiarity with Teradata, Microsoft SQL, GitHub or AWS viewed favourably.

· Understanding of statistical, econometric or predictive modelling techniques, such as logistic regression, macroeconomic modelling and machine learning.

· The ability to work with ambiguity, imperfect data and complex analytical problems in a practical, outcome-focused way.

· Clear written and verbal communication skills, including the ability to explain the conclusion, caveats and “so what” behind your analysis.

· Curiosity about AI and how it can be used responsibly to support analysis, documentation, learning and productivity.

Why CommBank

At CommBank, we believe growth drives innovation. Whether it’s refining your skills, collaborating with a dynamic community of experts, or solving the challenges that will shape the future, we offer opportunities to turn your potential into real impact.

This role offers the opportunity to build deep technical capability in a highly regulated and commercially important area of banking. You’ll gain exposure to credit risk models that are subject to strong scrutiny and used to support business and regulatory outcomes.

You’ll also work closely with business stakeholders and credit risk experts, giving you exposure beyond technical modelling and helping you understand how models are applied in real business contexts.

Advertising End Date: 20/08/2026