Model Analysis, Officer - Risk Capital, VP

Employment Type

: Full-Time

Industry

: Financial Services - Banking/Investment/Finance



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Assist model quants developing or enhancing Risk Capital/Stress Testing models Implement model analytics, model libraries/engine/executables and associated analytical tools, using programming languages such as C++, Python, VBA Test model performance, implement testing suites for new and existing models, establish automated testing processes and repeated model documentation processes Assist testing efforts and support requirements from Model Risk Management, participate in full model development, validation and ongoing performance monitoring cycles Partner with Finance and Risk Infrastructure (FRI) and IT to ensure that Risk Capital enhancements are correctly implemented and integrated in Citi’s Risk and Finance systems Qualifications: Masters and above degree in computer science, mathematics, financial engineering 5+ years of experience in an analytics/quantitative programming/implementation roles in a financial institution. Knowledgeable about risk measurement issues in market risk or credit risk a plus. Fewer years of experience will be considered with additional advanced degress (ex. PhD) Knowledge of risk capital and stress testing concepts and issues a plus. Strong communicator, self-starter, and team player Eagerness & ability to grasp complex analytical or mathematical concepts quickly Proficient in C++/C, Python, Excel VBA, Java and/or other programming languages Experience with model implementation and integration with technology systems Ability to nagivate through complex data and infrastructure environment a plus Experience with implementing analytical user tools such as what-if calculator in Excel or other UI form a plus Experience with database, cloud computing, client-server computing, distributed computing Exceptional candidates who do not meet all these criteria may be considered for the role provided they have the necessary skills and experience * The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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