A global investment bank is seeking a highly skilled and motivated Quantitative Analyst to join the XVACCR, Collateral & Credit Quantitative Research team. This role is central to the development of cutting-edge quantitative models and tools that support XVA pricing, counterparty credit risk, collateral management, and regulatory compliance.
You will work closely with desks across the bank including XVA, Risk, Collateral, and Credit Trading, contributing to strategic initiatives and regulatory projects such as XVAVaR, SACCR, FRTB-CVA, and RWA optimisation. This is a unique opportunity to be part of a dynamic team driving innovation in financial modelling and quantitative research.
This is a permanent role based in the City of London office (hybrid working - 3 days per week onsite).
Key Responsibilities
* Develop and implement pricing models and analytical tools for:
* Collateral Management (e.g., IMVA-CCP, SIMM)
* XVA-related activities (e.g., CVA, DVA, FVA, MVA)
* Collaborate with internal stakeholders including Trading, Risk, RPC, and IT to ensure model accuracy and performance.
* Contribute to the enhancement of XVA libraries and platforms to meet evolving regulatory requirements.
* Support the development of the Collateral Management platform for CCP and EMIR Initial Margin.
* Participate in system migration projects and optimisation initiatives using advanced modelling techniques (e.g., AAD, Machine Learning).
Candidate Profile
Essential Skills & Experience:
* Strong programming skills in C++.
* Solid understanding of numerical methods such as Monte Carlo simulations and optimisation algorithms.
* Experience with:
* Distributed computing and inter-process communication
* Multi-threading programming
* Microsoft Office, VC++, VBA
* SQL databases (Access, Oracle)
* Web technologies (XML, XSLT)
* Proven ability to work independently and as part of a team.
* Excellent analytical and problem-solving skills.
* Strong communication skills, both written and verbal.
* Creative and results-oriented with a proactive approach to learning and adapting.