Model Validation Specialist : IMM Pricing Model validation, AVP

Job Description

Model Risk Managements mission is to manage, independently and actively, model risk globally in line with the banks risk appetite with responsibility for: Performing robust independent model validation. Ensuring early and proactive identification of Model Risks. Designing and recommending model risk appetite. Effectively managing and mitigating model risks. Establishing Model Risks metrics. Designing and implementing a strong Model Risk Management and governance framework. Creating bank-wide Market Risk policies. IMM(Internal Model Method) is a risk management approach used by bank to calculate CCR exposure for derivatives, securities financing transactions(SFTs) and other financial instruments. The IMM Model Validation team as part of MoRM is responsible for independent review and analysis of all IMM forward pricing models used to calculate key components of IMM i.e. Potential Future Exposure (PFE), Expected Exposure (EE), Effective Expected Positive Exposure (EEPE). Your key responsibilities The role is to independently review and validate IMM forward pricing models. The role as a Quantitative analyst in Mumbai will work closely with validation team in Berlin and London to produce, analyse and document validation testing. Review and analysis require a good understanding of the derivative pricing models, implementation methods, derivative products and associated risks. The outcome of review and analysis and independent will form the basis of discussion with key stakeholders including : Front office quants, Market risk managers and Finance Controllers. Your skills and experience Excellent mathematical ability with an understanding of stochastic calculus, Partial differential equations, Longstaff-Schwartz Monte Carlo and Numerical Algorithms Strong understanding in financial markets (specially derivative pricing) demonstrated by qualifications and experience. Strong understanding of key matrices in IMM PFE, EE, EEPE, CVA, WWR Experience in model validation. Proficiency in Python coding. Excellent communication skills - both written and oral. Education/Qualifications Academic degree in a quantitative discipline (e.g. Mathematical Finance, Maths , Physics, Financial engineering).