Counterparty Risk Senior Model Validator

An exceptional opportunity has arisen for a Counterparty Risk Senior Model Validator to join a highly respected financial institution in London. This role is ideal for someone with a passion for quantitative analysis and a deep understanding of counterparty credit exposure, XVA models, and regulatory frameworks. You will play a pivotal part in ensuring the robustness and accuracy of complex risk models that underpin critical business decisions.

What you'll do:

As a Counterparty Risk Senior Model Validator based in London, you will be entrusted with the responsibility of safeguarding the integrity of sophisticated financial models that are central to managing counterparty credit exposures. Your daily activities will involve rigorous assessment of quantitative methodologies used in these models-ranging from reviewing simulation techniques to independently implementing benchmarks for product-specific features like CSAs and netting. You will document your findings comprehensively, ensuring transparency throughout the validation process while engaging constructively with stakeholders from various departments. Success in this role requires not only technical proficiency but also excellent interpersonal skills; you will regularly present your work at technical committees and contribute meaningfully to model governance initiatives. By participating in ongoing monitoring activities and responding thoughtfully to stakeholder inquiries, you will help maintain robust controls over model risks while supporting the organisation's broader strategic objectives.

• Validate counterparty credit exposure models and XVA models by conducting thorough reviews of risk factor simulation models, backtesting processes, and model calibration techniques to ensure their accuracy and reliability.
• Independently implement benchmark models tailored to specific products, incorporating features such as Credit Support Annexes (CSAs) and netting agreements to reflect real-world trading scenarios.
• Assess mathematical soundness and implementation quality of risk models by evaluating their strengths, weaknesses, assumptions, and limitations from both theoretical and practical perspectives.
• Document all aspects of model validation testing and findings meticulously, maintaining high standards in reporting while following up with relevant stakeholders on any identified modelling issues or concerns.
• Participate actively in technical committees by presenting comprehensive model validation documents and contributing valuable insights into ongoing discussions about model governance.
• Conduct model risk management activities including continuous monitoring of model performance as well as periodic re-validation to ensure ongoing compliance with internal policies and external regulations.
• Establish dependable working relationships with key stakeholders across front office, finance, and risk functions to facilitate effective communication regarding model-related queries and regular review schedules.
• Provide timely responses to stakeholder requests while balancing immediate needs against longer-term project goals to maintain alignment with organisational priorities.
• Engage in the validation of additional risk models beyond counterparty credit risk and XVA models as required by the evolving needs of the business.
• Develop your capability to communicate complex technical concepts clearly to diverse audiences including oversight bodies such as regulators, internal auditors, and external auditors.

What you bring:

To excel as a Counterparty Risk Senior Model Validator, you will bring an impressive academic background complemented by substantial practical experience in quantitative finance. Your expertise should encompass advanced mathematical techniques relevant to financial modelling alongside proven familiarity with regulatory frameworks governing counterparty credit risk. In addition to technical acumen-such as programming skills in C++-you will possess strong communication abilities that enable you to articulate complex concepts clearly when collaborating with colleagues or presenting findings at committee meetings. Your capacity for independent work combined with adaptability allows you to manage multiple priorities efficiently without compromising on quality or deadlines. A holistic appreciation for cross asset class products further enhances your ability to assess model suitability across varied contexts. Ultimately, your blend of analytical rigour, attention to detail, interpersonal sensitivity, and commitment to responsible model governance will set you apart in this challenging yet rewarding position.

• A postgraduate degree (Masters or PhD) in a quantitative discipline such as mathematics, physics, engineering or related field is essential for success in this role.
• Advanced understanding of quantitative methods including financial mathematics, stochastic processes, and Monte-Carlo simulation is required to effectively validate complex risk models.
• Extensive hands-on experience validating counterparty risk models-particularly Potential Future Exposure (PFE) and XVA models-is crucial for meeting regulatory expectations.
• Comprehensive knowledge of regulatory standards such as Basel III capital requirements and Standardised Approach for Counterparty Credit Risk (SACCR) is necessary for ensuring compliance.
• Proficiency in coding (preferably C++) along with practical experience using Excel enables efficient implementation and analysis of benchmark models.
• Familiarity with Adaptiv Analytics for PFE modelling as well as Murex systems for booking and risk management would be advantageous but not mandatory.
• Excellent written and verbal communication skills are vital for documenting validation processes clearly and interacting effectively with diverse stakeholders.
• Demonstrated ability to work independently while adapting flexibly to shifting priorities ensures consistent delivery against both short-term tasks and long-term projects.
• A broad understanding of cross asset class products supports comprehensive evaluation of model applicability across different trading environments.

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