Model Analytics Analyst II

• 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
• Defend 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

• 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 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
• 2-5 YEARS reporting & analytics experience
• At least 2 years of extensive experience in reporting (risk/marketing) in portfolio reporting, model monitoring, generating business insights

Experience in developing optimal/ automated solution of reporting processes using SAS, Excel VBA, Tableau

• Global Benefits
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