Quant jobs / Commonwealth Bank of Australia

Senior Data Scientist - Stress Testing Models

Develop credit stress-testing models at Commonwealth Bank. The role links macroeconomic scenarios to default, loss and exposure measures across retail and institutional portfolios.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Develop statistical credit-stress models and analyse scenario impacts.
Prepare complex datasets and test model sensitivities.
Document assumptions and support independent validation.

What they ask for

Required

Statistical or econometric modelling
R or Python
SQL and large-data analysis
Model interpretation
Technical communication

Preferred

Credit risk, IFRS 9 or IRB models

Education: Tertiary qualification in mathematics, statistics, econometrics, engineering, data science or a related quantitative subject; level not specified.
Experience: Strong relevant modelling experience; no minimum years stated. Advert closes 6 November 2026.
Languages and tools: R
Python
SQL
Teradata
AWS
Markets: credit

How to prepare

Estimate stressed credit losses using PD, LGD and EAD assumptions.
Compare time-series and panel-model behaviour across macro scenarios.
Document model limitations and out-of-time performance.

What to study

The Risk Quant roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Commonwealth Bank of Australia’s site before applying: requirements, location and pay can change after we check them.

View the posting on Commonwealth Bank of Australia’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Commonwealth Bank of Australia and doesn’t handle applications.