Quantitative Analyst - Model Validation

Direct message the job poster from McGregor Boyall

The primary mandate of the Model Validation team is to manage model risk across a broad range of business areas, including models used for derivatives valuation, market and credit risk management, liquidity, and capital computations. The team is responsible for independently reviewing models to ensure theoretical soundness, implementation accuracy, and appropriate use. The role involves evaluating model performance, identifying limitations, and helping stakeholders understand the associated risks.

• Perform independent validation and approval of quantitative models, raising and managing model validation findings.
• Conduct annual reviews and revalidations of existing models.
• Provide effective challenge to model assumptions, mathematical formulations, and implementation methodologies.
• Assess and quantify model risk to inform stakeholders and contribute to compensating control development.
• Contribute to strategic and cross-functional initiatives within the Model Risk function.
• Oversee ongoing model performance monitoring, including benchmarking, process verification, and outcome analysis.
• Communicate validation results, model limitations, and uncertainties to stakeholders and management.
• Contribute to automation and efficiency initiatives, including applications of AI and process optimization.

• MSc or preferably PhD in a quantitative discipline (e.g., Physics, Mathematics, Computer Science, Financial Engineering, Statistics).
• Strong understanding of Value-at-Risk (VaR) computation frameworks and Counterparty Credit Risk (CCR) modelling.
• Experience in model validation or development, particularly within risk or liquidity modelling contexts.
• Proficiency in Python (preferred) or similar quantitative programming languages.
• Strong analytical and communication skills, with the ability to provide practical solutions to complex challenges.
• Demonstrated ability to work collaboratively within a team-oriented environment.

• Deep understanding of liquidity risk frameworks and internal liquidity stress testing (ILST) methodologies.
• Experience validating or developing liquidity models, including cash flow projections, liquidity coverage ratio (LCR), and net stable funding ratio (NSFR) frameworks.
• Familiarity with regulatory expectations for liquidity risk management (e.g., Basel III, PRA, FED, or ECB guidelines).
• Ability to assess model performance under stressed conditions and evaluate model assumptions around funding profiles, behavioral deposits, and contingency funding.
• Knowledge of balance sheet and treasury modelling, including funding concentration and intraday liquidity risk.
• Experience working with liquidity data, scenario analysis, and backtesting of liquidity models.
• Strong quantitative and programming skills for implementing and testing liquidity models efficiently.

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

• Mid-Senior level

• Full-time

• Analyst
• Industries
• Investment Banking