Hybrid Assistant Vice President, Regulatory Model Monitoring Analytics

at Citi

• Job title: Assistant Vice President, Regulatory Model Monitoring Analytics
• Job type: Full Time
• Experience level: Lead
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Python, SQL, Tableau
• Location requirements: Hybrid, Mumbai, India

About the role

• 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.