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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). 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. This would include performance assessment, drill down root cause analysis for performance deterioration, coming up with mitigation action providing rational for continued usage of the model without business impact. 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; understanding the incremental benefit the models bring to Risk strategies. Explain model performance to second line (Model Risk Management) of defense providing rational of model performance deterioration (if any), 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.
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
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
understanding the incremental benefit the models bring to Risk strategies
Explain model performance to second line (Model Risk Management) of defense providing rational of model performance deterioration (if any), 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
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, Cognos
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
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
5+ YEARS reporting & analytics experience
At least 5 years of extensive experience in reporting (risk/marketing) in portfolio reporting, model monitoring, generating business insights
Experience in automating reporting processes
Nice to have:
Experience in automating reporting processes
Experience in developing optimal/ automated solution of reporting processes using SAS, Excel VBA, Tableau
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