Analyst- CCAR-CECL-Unsecured Production and Monitoring

Job Description

Analyst -C10- CCAR-CECL-Unsecured Production and Monitoring

This position will focus on model performance tracking, annual model review, production support, and model implementation of CCAR/DFAST/ICAAP and CECL stress loss models for Citi's unsecured portfolios, including credit cards, personal installment loans and ready credit.

Roles and Responsibility:

• Obtain modeling code from developers, implement in a production environment, and support UAT
• Download and process updated data from countries/regions and/or IT to run primary & benchmarking CCAR and CECL models to assist countries/regions in their use of the CCAR/DFAST/CECL models in business activities
• Run quarterly model performance back-testing, sensitivity analysis, and other required model performance analysis for production models
• Perform formal annual model review according to MRM’s guidance and standards. Respond to MRM’s questions as needed
• When forecast or performance shifts are observed, perform diagnostic analytics around drivers including standard reporting as well as drill down analytics
• Explain model results and review drivers of observed gaps or deterioration in model performance with regional/country risk managers and internal model development teams.
• Create code packages and document all production, implementation, and monitoring related activities including QA/QC steps in model documents and production/implementation/monitoring manuals

Qualifications

• Advanced Degree (Bachelor’s required and Master’s preferred) in Statistics, Computer Science, Applied Mathematics, Operations Research, Economics, or other highly quantitative discipline
• 2-5 YEARS production and monitoring experience
• Strong programming skills (SAS, R, Python, etc.)
• Expertise in model production, implementation, and model tracking processes across consumer products and/or business lines - international a plus
• Experience in developing automated production, reporting suite, and visualization tools preferred
• Basic understanding of modeling processes (regression, time series, decision tree, etc.) would be desirable.
• Expected to work with moderate supervision and guidance
• Good communication skill to explain technical information verbally and in writing to both technical and non-technical audiences, with attention to detail
• Work as an individual contributor

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