Manager, Credit Model Validation

Bluefin Resources; Sydney; Hybrid; AUD 140,000 - 190,000; Full time

Job summary

Bluefin Resources partners with a leading Australian bank to appoint an experienced Model Risk Manager. The role centres on independent validation of credit risk models across IRB, PD, EAD and LGD, including provisioning and scorecards.

You will own validation assignments, challenge methodologies and present findings to senior stakeholders. You’ll drive model governance, share knowledge within the team and support colleagues across retail and corporate portfolios.

Qualifications

• Minimum 4 years' Quantitative Analytics experience with strong exposure to Credit Risk.
• Strong understanding of IRB modelling, provisioning and scorecard methodologies.
• Proficiency in R, Python, SAS or equivalent.

Responsibilities

• Lead and deliver independent reviews of credit risk models across retail and non-retail portfolios.
• Evaluate model performance, methodologies, assumptions and implementation, identifying potential weaknesses and areas for enhancement.
• Undertake detailed assessments of IRB models, including PD, EAD and LGD, alongside provisioning, scorecard and stress testing models.
• Challenge existing modelling approaches and provide practical recommendations to strengthen model effectiveness and governance.
• Prepare clear, considered validation reports and present findings to relevant stakeholders.
• Provide technical guidance and knowledge sharing within the broader Model Risk team.

Skills

Quantitative analytics

Credit risk

IRB modelling

Model validation

Education

Applied Mathematics / Actuarial / Physics / Engineering degree

Tools

R

Python

SAS

Job description

Exciting Model Risk Manager opportunity with a leading Australian Bank.

• Two positions available
• Open to Sydney, Melbourne, Brisbane or Adelaide
• Attractive remuneration and employee benefits on offer

This is a full-time opportunity that requires a minimum of 2 days per week in the office and has the option be based in Sydney, Melbourne, Brisbane or Adelaide.

The Opportunity

We’re looking for an experienced Model Risk professional to join a high-performing team responsible for providing independent review and assurance across the bank’s credit risk modelling landscape.

You’ll be involved in the assessment of a diverse portfolio of models spanning retail and corporate lending, with particular exposure to IRB frameworks (PD, EAD and LGD), provisioning, scorecards and stress testing.

The role will see you take ownership of validation assignments, examining the robustness of model design, underlying methodologies and implementation. You’ll also have the opportunity to engage with senior stakeholders, provide independent recommendations and contribute to the ongoing development of the bank’s model governance practices.

With significant investment being made across the Model Risk function, this is an opportunity to work on complex, business-critical initiatives while broadening your exposure to evolving regulatory expectations and credit risk frameworks. You’ll also play an important role in sharing knowledge and providing technical support to colleagues.

Key Responsibilities:

• Lead and deliver independent reviews of credit risk models across retail and non-retail portfolios.
• Evaluate model performance, methodologies, assumptions and implementation, identifying potential weaknesses and areas for enhancement.
• Undertake detailed assessments of IRB models, including PD, EAD and LGD, alongside provisioning, scorecard and stress testing models.
• Challenge existing modelling approaches and provide practical recommendations to strengthen model effectiveness and governance.
• Prepare clear, considered validation reports and present findings to relevant stakeholders.
• Provide technical guidance and knowledge sharing within the broader Model Risk team.

Requirements:

• Excellent tertiary qualifications in an Applied Mathematical discipline e.g. Actuarial, Physics, Engineering etc.
• At least 4 years' Quantitative Analytics experience with strong exposure to Credit Risk
• Strong understanding of IRB modelling, provisioning and scorecard methodologies
• Technical proficiencies in R, Python, SAS or equivalent