Assistant Vice President Operations

Job Title: Model Risk Validation – Quantitative Modelling (Market/Credit/Derivatives)

Location: EMEA

Department: Enterprise Risk Management (ERM)

Function: Model Risk Management (MRM)

Role Overview

The Enterprise Risk Management (ERM) function is responsible for supporting the EMEA Chief Risk Officer in maintaining a robust and effective risk governance framework. A key component of this framework is the Model Risk Management (MRM) team, which provides oversight, governance, and independent validation of quantitative models used across the region.

MRM plays a critical role in ensuring the integrity and reliability of risk models that inform decision-making across asset classes and business lines, including environmental and social risk management. The team collaborates closely with Risk Analytics and Front Office quants to validate models used for risk measurement, pricing, and capital assessment.

Key Responsibilities

• Lead and perform

  independent model validation

  (initial and periodic) for a wide range of quantitative models, including:
• Derivatives pricing models
• Market and counterparty credit risk models
• Capital models (economic and regulatory)
• AI/ML models and corporate credit risk models (IRB, PD/LGD/EAD)
• Develop and prototype

  challenger models

  to benchmark and stress-test existing models.
• Conduct rigorous

  quantitative reviews

  of model frameworks, underlying assumptions, input data, and performance results.
• Perform technical testing of

  numerical implementations

  and conduct thorough

  documentation reviews

  .
• Ensure

  regulatory compliance

  and adherence to internal model governance policies.
• Produce detailed validation reports highlighting findings and

  recommendations for model improvements

  .
• Monitor the

  remediation of validation findings

  , ensuring timely and effective resolution.

Experience & Technical Competencies

Essential:

• Prior experience in

  quantitative modelling

  , either in development or validation, with exposure to one or more of the following:
• Market risk models (e.g., VaR, stressed VaR, IRC)
• Counterparty credit risk (e.g., CVA, PFE, SA-CCR)
• Derivatives pricing and valuation
• Strong knowledge of

  mathematics, statistics, and probability theory

  as applied in finance.
• Proficient in

  Python or R

  ; hands-on experience with simulation, numerical methods, and statistical inference techniques.
• Solid understanding of

  financial instruments

  , valuation principles, and risk metrics.

Preferred:

• Exposure to

  capital modelling

  (Basel regulations, ICAAP), credit risk models, or AI/ML model frameworks.
• Experience with

  C++, C#, or other compiled languages

  .
• Awareness of

  emerging trends

  in quantitative finance, regulatory changes, and advancements in risk modelling.

Educational Qualifications

• A postgraduate degree (Master’s or Ph.D.) in a

  quantitative discipline

  such as:
• Mathematics
• Statistics
• Mathematical Finance
• Econometrics
• Physics or related fields.