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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).
Job Responsibility:
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 heath of the model
Partnering 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 providing rational for model performance deterioration
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 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
Requirements:
Advanced Degree (Bachelors required or Masters preferred) in Statistics, Computer Science, Operations Research, Economics, etc.
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
Good communication skill to communicate 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.
2+ Years reporting & analytics experience
Extensive experience in reporting (risk/marketing) in portfolio reporting, model monitoring, generating business insights
Nice to have:
Experience in developing optimal/ automated solution of reporting processes using SAS, Excel VBA, Tableau will be a plus
Experience in adoption of AI in bringing efficiency into core functional process, automating reports would be a plus