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Regulatory Model Monitoring Analytics Intermediate Analyst

India, Bengaluru · Job Posted March 19, 2026
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Job Description

Citi’s Risk Modeling Solutions department is responsible for the development, delivery, and monitoring of all credit risk models across Citi’s consumer lending portfolios globally. The Regulatory Model Monitoring Analytics – C11 position sits within the Regulatory Model Monitoring & Analytics team.

Job Responsibility

  • 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
  • Communicate results to diverse audiences
  • 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
  • Support internal & external audits, and regulatory reviews by responding to model performance related inquiries
  • Conduct robust QC on model inputs, outputs, and monitoring datasets to maintain accuracy and reliability
  • Leverage Gen AI to establish consistent and scalable processes, driving automation and simplification initiatives
  • Work as an individual contributor in model monitoring techniques, analytical deep dives, and AI‑enabled insight generation

Requirements

  • Advanced degree preferred (Master’s required, PhD preferred) in Statistics, Applied Mathematics, Computer 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.
  • Experience in applying analytical and statistical methods to explain performance variation and derive actionable insights
  • Excellent written and verbal communication skills, with the ability to simplify complex topics for senior audiences
  • Extensive experience in model monitoring, development or validation for loss‑forecasting models (CCAR/CECL)
  • Experience in developing optimal or automated reporting solutions using SAS, Python, SQL, Excel VBA, Tableau and GenAI tools
  • 5+ years of experience in model monitoring, model development or validation, quantitative analytics, or related risk disciplines
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