Symphoni HR

The Corporate Institute; Mumbai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

The Corporate Institute in Mumbai seeks an experienced Risk Model Validation Associate to support independent validation of complex quantitative risk models for Counterparty Credit Risk, exposure simulation, and CVA/XVA within a global financial institution.

You will assess model soundness, calibrations, and performance; apply Monte Carlo methods, stochastic calculus, and statistical testing; and develop validation tools using Python, R, or VBA, collaborating with Model Risk and Front Office

Qualifications

• 3-5 years of experience in quantitative finance, model validation, or related area.
• Strong understanding of Counterparty Credit Risk (CCR) and exposure modelling concepts.
• Hands-on experience with Monte Carlo exposure simulation and CVA/XVA.
• Proficiency in Python, R, and/or VBA.
• Knowledge of stochastic calculus and numerical methods used in financial modelling.

Responsibilities

• Perform independent validation of CCR and related quantitative risk models.
• Assess methodologies, assumptions, limitations, and applicability to risk use cases.
• Review Monte Carlo exposure simulation methodologies and calculations.
• Support validation of CVA/XVA pricing and risk models across 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.
• Analyze model performance, identify weaknesses, and recommend remediation.
• Review model documentation and implementation details.
• Assess inputs, data quality, calibration approaches, and parameter assumptions.
• Develop validation tools, analytical frameworks, and test scripts using Python, R, VBA.
• Collaborate with Model Risk, Market Risk, CCR, Front Office Quant, Technology, and other controls.
• Support preparation of validation reports and remediation recommendations.
• Ensure alignment with regulatory frameworks and internal model governance.

Skills

Python

R

VBA

Monte Carlo methods

Statistics

Quantitative testing

Communication of findings

Collaboration

Education

Master's degree in Quantitative Finance

Advanced degree in related field

Tools

Python

R

VBA

Job description

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.