Model Monitoring, Analytics

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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 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, generating insights from different analysis required by business.
• People Manager

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.

Experience

• 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 automating reporting processes would be a plus.

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Job Family Group:

Risk Management

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Job Family:

Model Development and Analytics

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Time Type:

Full time

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Most Relevant Skills

Analytical Thinking, Business Acumen, Constructive Debate, Data Analysis, Escalation Management, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, Statistics.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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