
Position: Manager - Model Validation
Location: Bangalore
Position details:
This position is used for adverse consequences from decisions based on incorrect or misused model outputs and reports. Model risk can lead to financial loss, poor business and strategic decision-making, or damage to a banking organization's reputation. Model validation is the set of processes and activities intended to verify that models are performing as expected
The candidate will report to the Head of Model and EUCC Risk as part of the Model and EUCC Risk Center of Excellence.
Roles and Responsibilities:
- Independent testing and documenting validation results, including analyzing and interpreting statistical data, assessments of model conceptual soundness, evaluation of data and assumptions, testing model computational accuracy, and performing outcomes analysis (such as back-testing and benchmarking).
- Create findings as required, recommend management action plans, and validate remediation activities.
- Assess model changes to ensure continued performance of the model.
- Work with Model Owners to establish appropriate monitoring metrics and thresholds.
- Consult with model owners and users on the design of effective model operational controls.
- Execute activities in compliance with the Americas Model Risk Management Policy and Procedure as aligned to US regulatory expectations.
- Manage a team of validators, ensuring the quality, compliance, and timeliness of deliverables.
- Interact with counterparts in the Americas to remain aligned with program requirements.
Job Requirements
- Proven track record of strong technical model development or model validation with experience with models and modeling techniques in one or more of the following areas:
Market Risk
Counterparty Credit Risk
Wholesale Scorecards and Economic Capital
Capital Planning and Stress Testing
Financial Crimes, Compliance, Fraud
- Knowledgeable of model risk management and associated US regulatory requirements such as OCC 2011-12, FRB SR 11-7 is required.
- Bachelor 's degree in Economics, Finance, Business (MBA), Financial Engineering, Mathematics, Statistics or a related field (or foreign equivalent degree). Advanced degree preferred.
Technology Knowledge:
- Proficiency in one or more of the following tools: SAS, Python, R, MATLAB, C, SQL, Visual Basic, Bloomberg
- Academic or industry experience with exposure to the use of Artificial Intelligence (AI) and Machine Learning (ML) are preferred
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