Pricing Model Risk Quantitative Analyst - AVP

The EMEA Model Risk Management (EMRM) within ERM isresponsible for model governance and the validation of models usedby the bank in EMEA. This includes, among others, derivativepricing models, risk models used for risk measurement anddecision-making purposes, capital models, AI models, etc. EMRMworks closely with all stakeholders including Risk Analytics andFront Office quants to ensure that all models are validated on aperiodic basis as well as at inception and changes. EMRM providesregular model risk reporting to model oversight committees and theBoard. MAIN PURPOSE OF THE ROLE Independent model validation ofderivative pricing methodologies, both initial and periodic, acrossall asset classes and model types and in line with regulatoryrequirements and industry best practice. The validation regularlyrequires an independent implementation of the models and theimplementation of alternative challenger models. KEYRESPONSIBILITIES - Initial and periodic validation of pricingmodels - Designing, modelling and prototyping challenger models -Quantitative analysis and review of model frameworks, assumptions,data, and results - Testing models numerical implementations andreviewing documentations - Checking the adherence to governancerequirements - Documentation of findings in validation reports,including raising recommendations for model improvements - Ensuringmodels are validated in line with regulatory requirements andindustry best practice - Tracking remediation of validationrecommendations SKILLS AND EXPERIENCE Experience : Essential: - Atleast a first relevant experience in quantitative modelling (modeldevelopment or validation) of pricing models Optional: - Experiencein any of other model types (AI models, Market risk models,Counterparty credit risk models, Capital models) Competencies:Essential: - Good background in Math and Probability theory -applied to finance. - Good knowledge of Data Science andStatistical inference techniques. - Good understanding of financialproducts. - Good programming level in Python or R or equivalent. -Good knowledge of simulation and numerical methods - Awareness oflatest technical developments in financial mathematics, pricing,and risk modelling Beneficial: - Experience with C++ or C# orequivalent Optional: - Experience with AI models Education : - APostgraduate degree in a quantitative discipline (e.g., statistics,mathematics, mathematical finance, econometrics) PERSONALREQUIREMENTS - Strong problem solving skills - Strong numericalskills - A structured and logical approach to work - Excellentattention to detail - Excellent written and oral communicationskills - Ability to clearly explain technical matters - Apro-active, motivated approach