Model Monitoring and Business Analytics - Vice President

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.

Role:

The Model Monitoring Analytics – C13 position sits within the Decision Model Monitoring & Business Analytics team and is responsible for:

Core Responsibilities:

This position within Global Consumer Banking will focus on model performance Monitoring, Analytics & Insights for Non-Regulatory Decision Models for Unsecured products (e.g., Credit Cards). The responsibility includes but not limited to the following activities:

• Perform Root Cause Analysis explaining model performance to second line of defense and Policy teams for Business risk decisioning.
• Analyze & bring out Insights for Credit Risk Non-Regulatory Scoring/ Non-Scoring Segmentation models adding business value. This would include performance assessment, drill down root cause analysis for performance deterioration, mitigation action providing rational for continued usage of the model as applicable.
• Present model performance to senior stakeholders, CROs, Risk Policy managers, Sponsors explaining the heath of the model, connecting model metrices to business scenarios explaining the breach in model performance.
• Partnering with Risk Policy leads to help understanding the levers / cut off adjustments required in scores baked in Risk strategies to bring in incremental benefit / loss mitigation to business.
• Explain model performance to second line (Model Risk Management) of defense providing rational for model performance deterioration, explaining the applicability of the usage of the model.
• Respond to queries from 3rd Line of Defense (Internal and External Auditors) on model performance.
• Work effectively across cross functional teams - Development, Implementation, Policy, Validation and Governance teams - coordinating the horizontal model usage and maintenance activities.
• Perform analysis for benchmark models and other adhoc analysis as required by business/validation teams.
• Develop knowledge and drive discussions on Model usage across channels, score range with Risk Strategy managers.
• Conduct QA/QC on all steps (e.g., input data, model output, etc.) required for model monitoring and production forecast reporting.
• Deliver comprehensive write-up of ongoing model performance assessment, Annual Model Review / Revalidation documents.
• Understand model variables and economic forecasts and conduct drill down analysis and reporting of model performances.
• Deliver end user computing process related mandates.
• Expected to manage own projects independently.
• Train and mentor junior team members on Model Monitoring, generating insights from different analysis required by business.

Education:

Advanced Degree (Bachelors required or Masters preferred) in Statistics, Computer Science, Operations Research, Economics, etc. MBA s should apply only if they are interested in career in specialized quantitative risk management discipline.

Skillset

• Strong programming (SAS, SQL, Python, etc.) skills.
• Understanding of traditional modeling processes (linear/ logistic regression, segmentation, decision tree) and machine learning algorithms (Random Forest, Gradient Boosting, XG Boost, SVM, etc.), time series, linear/nonlinear optimization.
• Strong understanding of relevant model metrics / KPIs & bring out insights on model performance tracking.
• Good communication skill to be able to articulate technical information verbally and in writing to both technical and non-technical audiences is a must.
• Extensive experience in model monitoring/validation, performance scorecards, etc. in Excel, Tableau, Cognos, etc.
• Experience in developing optimal/ automated solution of reporting processes using SAS, Excel VBA, Tableau will be a plus.

Qualification:

• 10+ years of relevant experience in model analytics and insights.
• At least 7 years of extensive experience in model monitoring, generating business insights, analytical projects contributing business value
• Experience in adoption of AI in bringing efficiency into core functional process, automating reports would be a plus.

This is a Individual Contributor role

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