Global investment bank seeks a VP level Quant analyst as part of its expanding Counterparty Credit Risk Analytics function.
This role sits within the Counterparty Credit Risk Analytics Quant team that provides, maintains, and monitors models, data, and tools related to counterparty credit risk (CCR) of traded products, including models focused on both bilateral counterparty and central counterparty clearing (CCP) risk. CCRAQ supports the Credit Risk and Wholesale communities in understanding the risk drivers of material changes in model outputs.
Development, testing, documentation and maintenance of counterparty credit risk models: these will include risk factor simulation models, pricing models, aggregation models as well as back testing methodology
Support of the counterparty credit risk platform, including investigation and resolution of model-related system issues and practical quantitative support to model users
Improvements to model development infrastructure, such as test harnesses, support utilities, visualization tools
Partner with internal groups including Capital, Risk, Technology, Model Risk Management and Market Risk Management on model enhancement, performance testing and documentation to remediate internal and external requirements
Work in quantitative modelling on fixed income and/or commodity products on behalf of a global financial institution
Prepare developmental evidence and document to support internal and external exams
Identifying common themes across global markets along with improvement initiatives
Communicating the results of this analysis to all model stakeholders including risk management, model development, model risk, senior management and our regulators
Supporting model development in confirming remediation of model issues prior to their being taken live
Driving incremental improvement to our model performance assessment tool set across all business areas
Master's degree or PhD required (preferably in Mathematics, Statistics, Physics or related field) and 3-6 years' experience working in quantitative modelling in credit risk, CVA, model valitation, or front office model development within a global financial institution
Experience with mathematically sophisticated financial modelling, preferably in counterparty credit risk or XVA
Ability to express technical concepts clearly in written and spoken English
Programming skills: key languages are C++ and Python; a solid understanding of sound software development principles
Up-to-date knowledge of industry trends and developments, a commercial instinct, and an understanding of sound risk management principles
Good written and oral communication, interpersonal and organizational skills and ability to build and maintain relationships with personnel across areas and regions
Ability to multitask with excellent time management skills
Sense of focus and rigor in the completion of deliverables
Pro-active behaviour with capacity to seize initiative
Morgan McKinley is acting as an Employment Agency and references to pay rates are indicative.