The Institutional Credit Management (ICM) group is looking for a full-time lead/senior analyst to join its Counterparty Credit Risk (CCR) function. ICM has been established with the objective to provide an integrated “end-to-end” credit underwriting, identification, measurement, management and monitoring for wholesale credit businesses across the enterprise. This is exciting opportunity for an inquisitive, action-oriented, highly motivated individual looking to thrive and build a career in a highly visible, challenging, dynamic, and growing front-office division.
The Data Quality Remediation and Insights organization within ICM is responsible for driving a data architecture in order to deliver front to back design, identify gaps, and implement a robust control framework across ICG Wholesale Credit Risk (WCR) universe with a specific focus on counterparty credit risk. A key focus is on Data Quality including ensuring completeness, accuracy and timeliness across data flows and alignment with Citi’s overall data strategy. The Data group will also build a sustainable framework to perform intelligent analytics and mining on the data to identity patterns and correlations among data sets and quality metrics which can be transformed into actionable insights for the respective stakeholders including senior management, business, independent risk and operations functions.
The group is responsible for extensive partnering across all relevant businesses within ICG and Independent Risk to drive key initiatives and associated deliverables for the data strategy and manage change with the right governance framework. The function and role spans the counterparty credit risk group within the ICG organization and, as a result, requires strong engagement with relevant teams.
Required Skills and Qualifications:
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
Job Family Group:Decision Management
Job Family:Specialized Analytics (Data Science/Computational Statistics)
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