Analyzing and generating insights for regulatory risk models for Citi’s consumer lending portfolios. Collaborating across teams to ensure consistent model usage and compliance with regulations.
Responsibilities
Analyze and generate insights for Regulatory Risk Models (CCAR/DFAST/CECL/IFRS9 stress‑loss models), including performance assessment, root‑cause analysis for deterioration, recommended mitigation actions, and rationale for continued model usage.
Quantify and articulate the business impact of model performance trends—translating changes in model accuracy into impacts on loss forecasts, capital, and reserves.
Provide clear, data‑driven explanations that support decision‑making by senior stakeholders.
Communicate results to diverse audiences.
Present model performance to sponsors, developers and other senior stakeholders—explaining model health, linking metrics to business scenarios, and clarifying performance breaches.
Explain the model performance trends to Model Risk Management (MRM), including rationale for deterioration if observed.
Prepare and deliver comprehensive write-ups for Ongoing Monitoring Reports and Annual Model Review documentation.
Work effectively across cross‑functional teams—including Model Development, Implementation, Sponsors/Policy, Validation, and Governance— to ensure consistent model usage, aligned maintenance processes, and smooth execution of all model lifecycle activities.
Support internal & external audits, and regulatory reviews by responding to model performance related inquiries and providing transparent, well‑structured documentation.
Conduct robust QC on model inputs, outputs, and monitoring datasets to maintain accuracy and reliability.
Requirements
Advanced degree preferred (Master’s required, PhD preferred) in Statistics, Applied Mathematics, Compute Science, Operations Research, Economics, Finance (MBA), or another highly quantitative discipline.
Strong programming skills in SAS, SQL, Python; experience with Tableau/Excel for performance reporting.
Understanding of modeling techniques such as linear/logistic regression, machine learning techniques, segmentation, decision trees, survival models, time series analysis, etc.
Extensive experience in model monitoring, development or validation for loss‑forecasting models (CCAR/CECL).
Benefits
Champion the responsible deployment of Gen AI, embedding transparency, robust governance, and proactive compliance with evolving AI regulations to ensure compliant and ethical outcomes.
Mentor and support junior analysts in model monitoring techniques, analytical deep dives, and AI-enabled insight generation.
Contribute to a culture of analytical excellence, continuous improvement, and responsible innovation.
Job title
Assistant Vice President, Regulatory Model Monitoring Analytics
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