• Build statistical and machine learning models that help solve real commercial lending and customer problems.
• Join a highly experienced modelling team where you can develop specialist credit risk capability without needing previous credit risk experience.
• Work on high-impact initiatives spanning lending automation, merchant data, property analytics and model monitoring.

See Yourself In Our Team

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.

Do Work That Matters

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:

• Support the development of statistical and machine learning models across commercial lending and credit-related use cases.
• Work with data to investigate business problems, identify patterns and determine appropriate analytical approaches.
• Contribute to machine learning-based origination scorecards and statistical modelling, including logistic regression.
• Explore new data sources and methodologies, including merchant data, property analytics and forecasting.
• Support model monitoring, implementation and ongoing model management.
• Help translate analytical findings into meaningful customer and business outcomes.
• Work alongside experienced credit modelling specialists who can help you build your technical and domain expertise.

The team supports model implementation and works closely with the areas responsible for deployment, but does not own model deployment itself.

What you'll bring

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:

• Strong quantitative and analytical problem-solving skills.
• Practical experience using Python or R for analysis or modelling.
• An understanding of statistical modelling and/or machine learning, including how you move from a business problem through data preparation, model selection, testing and evaluation.
• An understanding of fundamental modelling concepts such as feature selection, data quality, data leakage and model performance.
• Curiosity about data and the ability to look beyond simply running a model or package to understand what the data is telling you and why it matters.
• The ability to take a problem that may not be completely defined, ask good questions and work towards a practical analytical solution.
• The ability to communicate your thinking clearly and work with stakeholders outside of analytics.
• A genuine appetite to learn and develop your technical and commercial understanding.

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.