Description
HSBC are recruiting for an experienced Quantitative Analyst - Counterparty Credit Risk/XVA Pricing. The Quantitative Analyst - Counterparty Credit Risk/XVA is responsible for fully designing, implementing and documenting the Dynamic Initial Margin Model in given Monte Carlo IMM framework.
The Key Accountabilities for the Quantitative Analyst - Counterparty Credit Risk/XVA Pricing:
- Ability to design and implement a model that addresses business requirements
- Ability to design and implement a model validation framework that assess model adequacy
- Ability to effective document the model following given standards
- Understanding of regulatory requirements means the business is forewarned of changes in the regulation and can prepare accordingly.
- Understanding of mathematical concepts behind CCR and Collateral models already implemented
- Ability to navigate through the existing analytical modules of CCR Aggregation and Collateral libraries
- Effective communication with the GRA team at both Regional and Group levels ensures there is a strong common understanding of the models and that best practices are being applied.
- Providing bespoke analysis for new business helps ensure that the business can make appropriate risk/capital assessments.
The Quantitative Analyst - Counterparty Credit Risk/XVA Pricing will have experience in:
- At least 10 [8] years of experience in CCR/XVA/Pricing Quantitative Analytics team. Having been personally involved in building simulation(Monte Carlo scenario generation) models and developing simulation solution
- Ideally previously involved in successful DIM implementation for IMM (and/or good to have DIM implementation for MVA)
- Previously involved or familiar with CCR backtesting for IMM
- Ideally previously involved in successful regulatory submissions
- Ability to lead, manage and successfully deliver projects within the agreed time scale, in liaison with all relevant stakeholders: model owners, credit, business, IT, senior management and regulators.
- Clear and demonstrable familiarity with ISDA SIMM, and good to have familiarity with other Initial Margin computation (as for instance, CCP IM)
- Clear and demonstrable familiarity key risk measures such as MVA, CVA, EPE, PFE.
- Minimum Masters level in Math/Computer Science/Engineering discipline
- Excellent understanding of Stochastic Calculus applied to quantitative finance and numerical optimisation technics
- Developer with demonstrable experience in python/JAVA/C++