Model Risk Mgmt-Analyst-Treasury & MR

Model Risk Analyst-ALM & IRRBB Model Risk Management

Function: Model Risk Management / Model Validation

Experience:4-7 years

About the Role

We are looking for an experienced professional to join our Model Risk Management team, with a primary focus on ALM Behavioral Models and Interest Rate Risk in the Banking Book (IRRBB) models.

This is a specialist role requiring hands-on experience in the development, validation, review, or monitoring of ALM/IRRBB models. The successful candidate will be expected to independently assess model methodologies, challenge assumptions, develop benchmarking/challenger approaches, and engage with model owners and senior stakeholders on model risk issues.

While the primary focus will be ALM Behavioural and IRRBB models, the role will also provide opportunities to gain exposure to Treasury Pricing, Market Risk Models, and broader Model Risk Management, allowing the candidate to build expertise across multiple areas of quantitative risk.

Key Responsibilities

ALM & IRRBB Model Validation

• Independently conduct validation and review of ALM behavioural and IRRBB models.
• Assess conceptual soundness, model methodology, assumptions, data, implementation, limitations, and performance.
• Perform pre-deployment validation, periodic reviews, model monitoring, and ongoing performance assessment.
• Developing challenger models and independent benchmarking approaches
• Assess model limitations and their potential impact on IRRBB measurement and ALM risk management.
• Review model documentation and ensure that key assumptions, methodologies, limitations, and model-use considerations are appropriately captured.
• Preparing validation reports and presenting findings to stakeholders and governance forums
• Mentoring junior team members

What We Are Looking For

Core requirement:

• 4-7 years of relevant experience with hands-on exposure to ALM/IRRBB model development, model validation, or model review.
• Strong practical understanding of ALM behavioural modelling and IRRBB methodologies.
• Direct experience with one or more of the following would be particularly relevant:
• NMD behavioural modelling
• Deposit decay modelling
• Prepayment or early redemption models
• IRRBB Methodologies
• ALM behavioural modelling and monitoring
• Strong quantitative and analytical skills with the ability to understand and challenge statistical/model methodologies.
• Experience with statistical analysis, model performance testing, benchmarking, and validation techniques.
• Knowledge of Python is desirable.
• Ability to work with large datasets and translate quantitative analysis into meaningful model-risk conclusions.

Educational Background

A postgraduate or undergraduate degree in Engineering, Mathematics, Statistics, Economics, Finance, or a related quantitative discipline is preferred.

Professional qualifications such as FRM, CFA, BTRM would be an advantage.