Model Analysis, Officer- Risk Capital, VP

Key Responsibilities: Risk Capital is a firm-wide metric to measure economic capital usage at the consolidated group and CBNA levels as well at the relevant detailed levels such as country, other legal entity and business unit. It is reported to regulators and the Board as a key capital adequacy metric for Citigroup and its major legal entities (MLE). Risk Capital is also used extensively in the ICG, CCB and GCRM to set risk limits and to assess the risk-adjusted profitability of large transactions. Risk Capital is increasingly visible to Citi’s business leaders because it is being used to allocate Tangible Common Equity (TCE) on a firm-wide basis globally. Allocated TCE is a critical input in one of the core measures of business profitability (RoTCE). The go-live of this new measure will increase the visibility of Risk Capital as well as the priority for Risk Capital enhancements. Key Responsibilities:

• Manage and track projects, initiatives, testing, remediation and model updates associated with IRRBB Risk capital
• 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
• Build and enhance data/analytical capabilities for Risk Capital, Risk Appetite Ratio and Stress Testing in support of internal clients’ needs
• Partner with Technology, Treasury Risk and Reporting to remediate model limitation and enhance Risk Capital and Risk Return Monitoring & reporting capability
• Partner with Technology and Project Management Group to implement model change and capability enhancing projects

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 degrees (eg. 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 navigate through complex data and infrastructure environment a plus

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Job Family Group:

Risk Management

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Job Family:

Risk Analytics, Modeling, and Validation

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Time Type:

Full time

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