XVA Model Validation Quant - Quanteam

Who We Are Looking For

Quanteam UK are seeking an XVA Model Validation Quant to join our Model Risk and Validation practice. The successful candidate will be responsible for the independent review, challenge and validation of XVA pricing and risk models, ensuring they are conceptually sound, correctly implemented and fit for purpose within the applicable regulatory and model risk management frameworks.

*Proven XVA knowledge and expertise is essential for this role.

Key Responsibilities

1. Performing independent validation of XVA models, including CVA, DVA, FVA, ColVA, MVA and KVA, covering model theory, assumptions, calibration and implementation.
2. Reviewing the underlying exposure simulation framework, including risk factor models, Monte Carlo engines, netting and collateral modelling.
3. Building independent benchmark and challenger models to test model outputs, sensitivities and numerical stability.
4. Assessing model limitations, conducting stress, sensitivity and backtesting analysis, and proposing model reserves or adjustments where appropriate.
5. Evaluating models against regulatory requirements, including SA-CVA, BA-CVA and CCR-related frameworks.
6. Producing clear and well-structured validation reports and presenting findings to model owners, risk committees and senior stakeholders.
7. Monitoring the remediation of validation findings and supporting periodic model reviews and change assessments.

Technical Competence

1. Essential: in-depth knowledge of XVA methodologies, including CVA, DVA, FVA, MVA and KVA, and their pricing, hedging and risk management.
2. Sound understanding of counterparty credit risk, exposure metrics (EE, EPE, PFE), wrong-way risk, collateral agreements and initial margin (including SIMM).
3. Strong grounding in derivatives pricing across one or more asset classes, such as rates, FX, credit or equities.
4. Solid knowledge of stochastic calculus, Monte Carlo simulation and numerical methods, including American Monte Carlo techniques.
5. Proficiency in Python and/or C++ for building independent replication and benchmarking tools.
6. Familiarity with model risk management frameworks and regulatory expectations for model validation.
7. Advanced degree (MSc or PhD) in a quantitative discipline such as Mathematics, Physics, Financial Engineering or a related field.

Behavioural Competence

1. Independent and objective, with the confidence to provide credible challenge to model developers and the business.
2. Rigorous and detail-oriented approach to analysis and documentation.
3. Clear written and verbal communication, with the ability to explain complex technical matters to non-specialist audiences.
4. Structured problem-solving skills and the ability to prioritise and manage multiple reviews to deadline.
5. Collaborative, with the ability to work effectively across Front Office, Risk and Quantitative Research teams.