Model Monitoring, Business Analytics – Analyst II

Role Overview

• 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.
• Present model performance to senior stakeholders, CROs, Risk Policy managers, Sponsors explaining the health of the model.
• Partner with Risk Policy leads to help understanding the levers / cut off adjustments required in scores baked in Risk strategies.
• Explain model performance to second line (Model Risk Management) of defense.
• 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.
• Perform analysis for benchmark models and other ad hoc 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.

Requirements

• Advanced Degree (Bachelors required or Masters preferred) in Statistics, Computer Science, Operations Research, Economics, etc.
• MBA should apply only if they are interested in career in specialized quantitative risk management discipline.
• Strong programming (SAS, R, Python, etc.) skills.
• Experience in reporting tools
• Excel, Tableau.
• 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.
• Understanding of relevant model metrics / KPIs & bring out insights on model performance tracking.
• 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.
• 2+ Years reporting & analytics experience.
• Extensive experience in reporting (risk/marketing) in portfolio reporting, model monitoring, generating business insights.
• Experience in adoption of AI in bringing efficiency into core functional process, automating reports would be a plus.

Tech Stack

• Cognos
• Python
• Tableau
• VBA

Benefits

• Citi is an equal opportunity employer
• Qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
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