Model Risk Quant - AVP

Independent model validation of quantitative methodologies, both initial and periodic, across all asset classes and model types (derivative pricing models, credit and market risk, capital models, AI models, etc. ) and in line with regulatory requirements and industry best practice. The validation regularly requires an independent implementation of the models and the implementation of alternative challenger models.

KEY RESPONSIBILITIES

• Initial and periodic validation of quant models
• Designing, modelling and prototyping challenger models
• Quantitative analysis and review of model frameworks, assumptions, data, and results
• Testing models numerical implementations and reviewing documentations
• Checking the adherence to governance requirements
• Documentation of findings in validation reports, including raising recommendations for model improvements
• Ensuring models are validated in line with regulatory requirements and industry best practice
• Tracking remediation of validation recommendations

SKILLS AND EXPERIENCE

Essential:

• At least a first relevant experience in quantitative modelling (model development or validation) in one or more of these topics:
  • Market risk models
  • Counterparty credit risk models
  • Derivatives pricing models

Optional:

• Capital models (Economic/Regulatory)
• Corporate credit risk models (IRB, PD/LGD/EAD)

Competencies:

Essential:

• Good background in Math and Probability theory - applied to finance.
• Good knowledge of Data Science and Statistical inference techniques.
• Good understanding of financial products.
• Good programming level in Python or R or equivalent.
• Good knowledge of simulation and numerical methods
• Awareness of latest technical developments in financial mathematics, pricing, and risk modelling

Beneficial:

• Experience with AI models
• Experience with C++ or C# or equivalent

Optional:

• Up-to-date knowledge of regulatory capital requirements for market and credit risk

Education :

• A Postgraduate degree in a quantitative discipline (e.g., statistics, mathematics, mathematical finance, econometrics)

PERSONAL REQUIREMENTS

• Strong problem solving skills
• Strong numerical skills
• A structured and logical approach to work
• Excellent attention to detail
• Excellent written and oral communication skills
• Ability to clearly explain technical matters
• A pro-active, motivated approach