Model Risk Management Senior Analyst

InterQuest Financial Markets; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A UK-based financial institution is seeking a Senior Model Risk Analyst to join its Risk function. This role involves independent validation of regulatory and non-regulatory models, enhancing the Model Risk Management Framework, and collaborating with quantitative teams. The ideal candidate will have substantial experience in financial services and a degree in a quantitative discipline. Skills in SAS, Python, or SQL are essential. The position offers a chance to work in a dynamic environment focused on model risk management.

Qualifications

• Experience in model validation, model risk management or a quantitative risk discipline.
• Familiarity with model risk guidance such as SR11-7, SS1/23 and SS3/18.
• Ability to communicate complex technical information to non-technical audiences.

Responsibilities

• Perform independent validation and periodic reviews of models in the firm's inventory.
• Support the development of the Model Risk Management Framework.
• Identify and manage key model risks in line with the firm's risk appetite.
• Collaborate on ICAAP, stress testing and model performance assessments.

Skills

Experience in financial services

Knowledge of IRB regulatory requirements

Proficient in SAS, Python, SQL or R

Strong analytical and problem-solving skills

Education

Degree in Mathematics, Statistics, Data Science or Engineering

Job description

An established UK-based financial institution is looking to appoint a Senior Model Risk Analyst within its central Risk function. The successful candidate will join a specialist Model Risk Management (MRM) team responsible for maintaining the organisation's framework for model governance, validation, and independent oversight across all risk categories.

This role will focus on the independent review and validation of regulatory and non-regulatory models, supporting the broader aim of ensuring that model risk is appropriately identified, managed, and monitored across the business.

Key Responsibilities

• Perform independent validation and periodic reviews of models held in the firm's model inventory, including IRB, ICAAP and ILAAP models, as well as other quantitative or deterministic methodologies.
• Support the ongoing development and enhancement of the Model Risk Management Framework, ensuring compliance with relevant regulatory standards and internal governance expectations.
• Identify, assess, and monitor key model risks, ensuring these are appropriately managed in line with the firm's risk appetite.
• Collaborate with risk and quantitative teams on ICAAP, stress testing and model performance assessments.
• Present validation results, findings, and recommendations to internal committees and senior stakeholders.
• Maintain up-to-date awareness of regulatory developments and best practices in model risk management.

Ideal Candidate

• Experience working in financial services, ideally within model validation, model risk management, or a quantitative risk discipline.
• Knowledge of IRB regulatory requirements (CRR, EBA, PRA) and familiarity with model risk guidance such as SR11-7, SS1/23 and SS3/18.
• Educated to degree level (or equivalent) in a quantitative discipline such as Mathematics, Statistics, Data Science or Engineering.
• Practical experience using one or more statistical programming tools (SAS, Python, SQL or R).
• Strong analytical and problem-solving skills with the ability to communicate complex technical information effectively to non-technical audiences.
• Proactive, organised and able to work both independently and collaboratively.

InterQuest Group is acting as an employment agency for this vacancy. InterQuest Group is an equal opportunities employer and we welcome applications from all suitably qualified persons regardless of age, disability, gender, religion/belief, race, marriage, civil partnership, pregnancy, maternity, sex or sexual orientation. Please make us aware if you require any reasonable adjustments throughout the recruitment process.