Senior Quant, Credit & XVA Model Validation, (VP), London

Ref: XVMV-2806
£££ Highly Competitive Salary Package
Leading Global Investment Bank
Structured Credit (Credit-Linked, CDS, Swaps, CDS, etc), XVA models, C++, Python

Our client, a leading Investment Bank, seeks to recruit a senior (VP) Quant Analyst to join its model risk department to play a lead role across Credit & XVA.  Based in London, you will work on the validation of derivatives pricing models and assessment of all associated model risk. This is an excellent leadership opportunity to work on cutting edge models in a highly quantitative global environment.


  • Review and validation of front office derivative pricing models, focussed on Credit and XVA models.
  • Implementation of benchmark models (C++) and testing scripts 
  • Development of alternative models and methodologies in order to assess model risk.
  • Day to day support of stakeholders in all model related questions.
  • Liaise with trading, front office quantitative analysts and developers, and market risk and valuation control analysts, to ensure speedy review and validation of new models and methodologies.
  • Maintain a team for identifying and quantifying model risk. For example, by performing interviews.


  • Experience in XVA (CVA, FVA, MVA, etc) and/or credit modelling (flow, vanilla and structured credit products.
  • Knowledge of stochastic calculus, financial mathematics for derivatives pricing, and associated numerical methods, e.g. Monte Carlo, PDEs and numerical integration.
  • Experience of implementing large projects in C++ 
  • Sound judgement in assessing the strength and weaknesses of modelling approaches.
  • Strong communication skills and ability to work effectively as part of a Global Team and to liaise with key stakeholders. Fluency in written and spoken English.
  • Strong writing skills with an ability to consistently produce precise, accurate and concise documentation.
  • Higher degree (MSc, PhD, DEA) in highly numerical subject such as mathematics or physics. A PhD is preferred.