# Senior Data Scientist - Stress Testing Models at Commonwealth Bank of Australia

Commonwealth Bank of Australia is hiring a Senior Data Scientist - Stress Testing Models. Level rates it Little AI ●○○○; you can [apply on Commonwealth Bank of Australia](https://jobsbylevel.com/go/2c2ee54b-a67e-4e84-b1a0-65cfea949645?utm_medium=ai-agent).

AI Level 1, AI centrality 30 out of 100. Sydney CBD Area.

## Details

- Company: [Commonwealth Bank of Australia](https://jobsbylevel.com/companies/commonwealth-bank-of-australia)
- AI level: AI Level 1 (score 30 out of 100)
- Location: Sydney CBD Area
- Posted: October 30, 2026
- Apply: https://jobsbylevel.com/go/2c2ee54b-a67e-4e84-b1a0-65cfea949645?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-data-scientist-stress-testing-models-at-commonwealth-bank-of-australia-f16efc

## Prepare for this job

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## Description

Model how credit portfolios respond under stress Apply advanced statistics to real-world risk challenges Turn complex modelling into meaningful risk insights See Yourself in Our Team The Model Development Chapter Area sits within Risk Management and is responsible for developing credit risk models and advanced analytics across the Group. You’ll join a collaborative modelling environment, working with colleagues across model development, independent model validation, business unit risk, Finance and Enterprise Services. Your work will span retail and non-retail credit exposures, giving you the opportunity to tackle complex modelling challenges across different portfolio types and understand how changing economic conditions can affect their risk profiles. Your Impact and Contribution How might changing economic conditions affect the credit quality of a portfolio? Where are its vulnerabilities, and how could losses evolve under different scenarios? As a Senior Data Scientist – Stress Testing Models, you’ll use advanced quantitative modelling and analytics to help answer these questions across CommBank’s retail and non-retail portfolios. Your work will support enterprise stress testing and planning, while providing meaningful insight into the drivers of portfolio risk, resilience and potential credit losses. This is an opportunity to combine deep quantitative thinking with real-world application, using data, statistical techniques and emerging AI tools to solve complex modelling problems and help inform important risk and business decisions. In this role, you will: Lead the development and enhancement of credit risk stress-testing models used across the Group. Build statistical models and conduct advanced analysis using techniques such as predictive modelling, non-linear regression, time-series analysis, panel-data methods and macroeconomic modelling. Translate macroeconomic and portfolio scenarios into credit risk impacts, including changes in Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD) and expected credit loss. Analyse model behaviour, sensitivities, limitations and key risk drivers to understand what stress-testing results mean for portfolio resilience and risk decisions. Work with large, complex and sometimes imperfect datasets, applying sound judgement to identify practical and well-governed approaches to data challenges. Use R, Python and SQL, alongside tools and platforms including Teradata and AWS, to prepare, transform and analyse data for modelling. Clearly articulate modelling methodologies, assumptions, limitations and conclusions so your work can be understood, challenged and independently validated. Partner with model users, independent model validation, business unit risk teams, Finance and Enterprise Services throughout the modelling lifecycle. Provide technical guidance and constructive review to other analysts, contributing to strong modelling standards and reusable analytical practices. Explore responsible applications of AI to enhance analysis, model development, documentation, learning and productivity, while maintaining accountability for final outcomes. What You’ll Bring You’re a naturally curious quantitative thinker who enjoys getting beneath the numbers. You can take an ambiguous modelling problem, work through complex or imperfect data, test different approaches and reach a well-reasoned conclusion. Just as importantly, you can explain what your analysis means and why it matters, whether you’re speaking with another modeller or a non-technical stakeholder. You’ll bring a combination of: Strong experience in quantitative statistical modelling, data science, econometrics or credit risk analytics, with the ability to independently solve complex modelling and data problems. Strong knowledge of statistical, econometric or predictive modelling techniques, which may include logistic and non-linear regression, time-series analysis, panel modelling, macroeconomic modelling and

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