Risk Model Validation Associate - Counterparty Credit Risk - Banking/Financial Services

Job location: [{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mumbai","addressCountry":"IN"}}] Work arrangement: Employment type: FULL_TIME Salary: "" Experience requirements: {"monthsOfExperience":36,"educational":{"credentialCategory":"bachelor degree"}} Education requirements: "" Role Overview: We are looking for an experienced Risk Model Validation Associate to support the independent validation of complex risk models within a global financial institution. The role will focus on assessing the conceptual soundness, performance, accuracy, and robustness of quantitative models used for Counterparty Credit Risk (CCR), exposure simulation, and CVA/XVA, while ensuring alignment with applicable regulatory expectations. Key Responsibilities: - Perform independent validation of Counterparty Credit Risk (CCR) and related quantitative risk models. - Assess model methodologies, assumptions, limitations, implementation approaches, and applicability to the intended risk use cases. - Review and validate Monte Carlo exposure simulation methodologies and calculations. - Support validation of CVA/XVA pricing and risk models across relevant financial products. - Apply stochastic calculus, numerical methods, statistics, and quantitative techniques to model validation and analysis. - Perform quantitative testing, benchmarking, sensitivity analysis, back-testing, and stress testing of risk models. - Analyze model performance, identify weaknesses and limitations, and recommend appropriate remediation. - Review model documentation, technical specifications, methodology papers, and implementation details. - Assess model inputs, data quality, calibration approaches, and parameter assumptions. - Develop validation tools, analytical frameworks, and test scripts using Python, R, VBA, or equivalent technologies. - Collaborate with Model Risk, Market Risk, Counterparty Credit Risk, Front Office Quant, Technology, and other control functions. - Support preparation of model validation reports, findings, observations, and remediation recommendations. - Ensure model validation activities are aligned with relevant regulatory frameworks and internal model risk governance standards. - Contribute to continuous improvement of model validation methodologies, quantitative testing frameworks, and risk analytics. Requirements: - 3 - 5 years of experience in quantitative finance, model validation, model risk management, counterparty credit risk, derivatives modelling, or a related area. - Strong understanding of Counterparty Credit Risk (CCR) and exposure modelling concepts. - Hands-on experience or strong working knowledge of Monte Carlo exposure simulation and CVA/XVA. - Good understanding of stochastic calculus and numerical techniques used in financial modelling and derivatives pricing. - Strong quantitative and analytical skills, including probability, statistics, numerical methods, and financial mathematics. - Hands-on programming experience in Python, R, and/or VBA. - Good knowledge of financial markets and derivative products, particularly interest-rate and other OTC derivatives. - Understanding of model validation concepts including benchmarking, sensitivity analysis, back-testing, stress testing, and model limitations. - Familiarity with regulatory expectations such as Basel III, CRD IV, and PRA Supervisory Statement SS1/23. - Strong documentation, analytical reasoning, and problem-solving skills. - Ability to challenge model assumptions constructively and communicate quantitative findings clearly. - Strong collaboration skills and ability to work effectively with global stakeholders. Good to Have: - Exposure to AI/ML techniques applied to risk modelling, model validation, or financial analytics. - Experience with XVA analytics, collateral modelling, wrong-way risk, or exposure profiles. - Familiarity with model risk management frameworks within global banks or financial institutions. - Master's degree or advanced qualification in Quantitative Finance, Financial Engineering, Mathematics, Statistics, Physics, or a related discipline.