Regulatory Model Monitoring Analytics Intermediate Analyst

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Job Overview

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.  These models span two core activities; granting and managing credit to individual customers and delivering loss forecasts for stress testing (ex. CCAR), loan loss reserving (ex. CECL), and business planning.  The Regulatory Model Monitoring Analytics – C11 position sits within the Regulatory Model Monitoring & Analytics team and is responsible for the following:

• 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.
• Leverage Gen AI to establish consistent and scalable processes, driving automation and simplification initiatives. Champion the responsible deployment of Gen AI, embedding transparency, robust governance, and proactive compliance with evolving AI regulations to ensure compliant and ethical outcomes.
• Work as an individual contributor in model monitoring techniques, analytical deep dives, and AI‑enabled insight generation. Contribute to a culture of analytical excellence, continuous improvement, and responsible innovation.

Education:

• Advanced degree preferred (Master’s required, PhD preferred) in Statistics, Applied Mathematics, Compute Science, Operations Research, Economics, Finance (MBA), or another highly quantitative discipline.

Skillset

• 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.

Experience

• 5+ years of experience in model monitoring, model development or validation, quantitative analytics, or related risk disciplines.

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Job Family Group:

Risk Management

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Job Family:

Model Development and Analytics

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Time Type:

Full time

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Most Relevant Skills

Analytical Thinking, Business Acumen, Constructive Debate, Data Analysis, Escalation Management, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, Statistics.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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