Counterparty Credit Risk Model Validation Specialist.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global investment bank with a significant presence in international financial markets. They are known for their commitment to excellence, rigorous risk management frameworks, and a collaborative culture that fosters professional growth. The firm operates at the intersection of complex financial services and innovative technology, maintaining a strong reputation for stability and strategic market influence.
About the role.
This role focuses on the independent validation of counterparty credit risk models to ensure they are robust, accurate, and compliant with regulatory standards. You will work closely with quantitative teams to assess model performance, identify potential risks, and provide critical insights that support the firm's risk management strategy. This is a high-impact position requiring deep technical expertise and a strong understanding of financial modeling within a banking environment.
What you will do.
- Perform independent validation of counterparty credit risk models, including CVA, IMM, and collateral models.
- Conduct rigorous quantitative testing and sensitivity analysis to evaluate model performance and limitations.
- Document validation findings and communicate results effectively to stakeholders and senior management.
- Ensure all models comply with internal policies and external regulatory requirements.
- Collaborate with model developers to address identified issues and improve model robustness.
- Monitor model performance through ongoing review and backtesting processes.
- Stay updated on industry best practices and regulatory developments in credit risk modeling.
What you bring.
- 6–18 years of experience in quantitative risk management or model validation within the banking sector.
- Strong academic background in Mathematics, Statistics, Financial Engineering, or a related quantitative field.
- Deep understanding of counterparty credit risk concepts, including CVA, EPE, and PFE.
- Proficiency in programming languages such as Python, C++, or R for quantitative analysis.
- Proven ability to interpret complex financial models and translate findings into actionable insights.
- Excellent communication skills with the ability to present technical information to non-technical stakeholders.
- Experience working in a hybrid environment with cross-functional global teams.
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