Credit Risk Modeler: Stress Tests & PD/LGD

Commonwealth Bank; Melbourne; In loco; AUD 140.000 - 190.000; Tempo pieno

Descrizione del lavoro

Commonwealth Bank in Melbourne seeks a Data Scientist - Credit Risk Models to develop and enhance credit risk models and stress-testing methodologies. You will work with complex data, applying advanced statistical techniques to quantify portfolio vulnerabilities and inform risk decisions.

You’ll contribute to PD/LGD/EAD, IRB and IFRS 9 related modelling, collaborating with risk and validation teams, and leveraging R, Python, and SQL across cloud platforms.

Competenze

• Tertiary qualification in a quantitative discipline with strong quants modules.
• Experience in quantitative modelling, data science, econometrics, or credit risk analytics.
• Strong foundations in statistical and predictive modelling with regression, time-series, macro modelling.
• Hands-on programming using R and/or Python, with SQL experience.
• Ability to work through ambiguous analytical problems and derive well-reasoned conclusions.
• Strong written and verbal communication to explain methodology and implications.
• Curiosity, sound judgement and willingness to learn new modelling approaches.
• Experience with credit risk modelling (PD/LGD/EAD, IRB, IFRS 9, or stress testing) desirable.

Mansioni

• Develop and enhance credit risk stress-testing models using advanced statistical techniques.
• Apply predictive modelling, regression, time-series analysis, panel-data methods and macroeconomic modelling.
• Translate economic and portfolio scenarios into measurable credit-risk impacts (PD, LGD, EAD).
• Analyse model behaviour, sensitivities, limitations and key risk drivers.
• Work with large and complex datasets, including incomplete data, with governed analytical approaches.
• Use R, Python and SQL, and cloud platforms to prepare data and develop models.
• Translate complex modelling outcomes into clear insights for technical and non-technical stakeholders.
• Document methodologies, assumptions and modelling decisions for independent review.
• Partner across modelling lifecycle with users, validation and risk teams.
• Explore uses of AI and emerging tools while maintaining human judgement.

Conoscenze

Quantitative problem-solving

Statistical modelling

Data analysis

Strong communication

Curiosity & judgement

Explain methodology

Formazione

Bachelor's degree in Mathematics/Statistics/Econometrics/Engineering/Data Science

Strumenti

R

Python

SQL

Descrizione del lavoro

Commonwealth Bank in Melbourne seeks a Data Scientist - Credit Risk Models to develop and enhance credit risk models and stress-testing methodologies. You will work with complex data, applying advanced statistical techniques to quantify portfolio vulnerabilities and inform risk decisions.

You’ll contribute to PD/LGD/EAD, IRB and IFRS 9 related modelling, collaborating with risk and validation teams, and leveraging R, Python, and SQL across cloud platforms.