
at Citi
Bulge Bracket Investment BanksPosted 6 days ago
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**Unsecured Regulatory Model Monitoring Analytics – Analyst II** Monitor and analyze credit risk models, driving insights and data-driven decisions. Key responsibilities include performance assessment, trend quantification, stakeholder communication, and model lifecycle management. Required skills: advanced degree in quantitative field, strong programming skills in SAS, SQL, Python, understanding of modeling techniques, and excellent communication skills. 2+ years of experience in model monitoring, development or validation for loss-forecasting models (CCAR/CECL).
- Compensation
- Not specified
- City
- Mumbai, Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Unsecured Regulatory Model Monitoring Analytics Analyst II
Discover your future at Citi
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Job Overview
Description:
Citis Risk Modeling Solutions department is responsible for the development, delivery, and monitoring of all credit risk models across Citis 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 C10 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 stressloss models), including performance assessment, rootcause analysis for deterioration, recommended mitigation actions, and rationale for continued model usage.
- Quantify and articulate the business impact of model performance trendstranslating changes in model accuracy into impacts on loss forecasts, capital, and reserves. Provide clear, datadriven explanations that support decisionmaking by senior stakeholders.
- Communicate results to diverse audiences. Present model performance to sponsors, developers and other senior stakeholdersexplaining 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 crossfunctional teamsincluding 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, wellstructured 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 AIenabled insight generation. Contribute to a culture of analytical excellence, continuous improvement, and responsible innovation.
Education:
- Advanced degree preferred (Masters 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 lossforecasting models (CCAR/CECL).
- Experience in developing optimal or automated reporting solutions using SAS, Python, SQL, Excel VBA, Tableau and GenAI tools.
Experience
- 2+ 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------------------------------------------------------
Job Family:
Model Development and Analytics------------------------------------------------------
Time Type:
Full time------------------------------------------------------
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.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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