Senior Consultant, Model Validation(Model Risk) at Northern Trust

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Banking, Financial ServicesIndustries

Requirements

8 - 10 years of modeling or quantitative analysis experience
Advanced proficiency in financial models used in portfolio analysis, asset management, Value at Risk, Monte Carlo, CAPM, Factors
Solid understanding of risks posed by AI/ML models (Fairness, Privacy, Transparency, Explainability, etc.)
Good understanding of stress testing, CCAR, CECL, etc
Validates models developed in Python or R (occasionally SAS); able to challenge conceptual soundness of regression and machine learning models and assure appropriate, good quality data usage
Develops and maintains understanding of algorithms across supervised learning, unsupervised learning, and time series analysis
Utilizes expertise in machine learning algorithms and statistics

Responsibilities

Act as lead contributor in discovery and diagnostic of model-related risks (input data, assumptions, conceptual soundness, methodology, outcomes analysis, benchmarking, monitoring, model implementation)
Validate models, challenge conceptual soundness of regression and machine learning models, assure data quality
Perform reviews of bank-wide quantitative models (CECL, CCAR/DFAST stress testing, credit risk loss projections (PD, LGD, EAD), operational risk, interest rate risk, AML/Fraud Detection, machine learning models)
Ensure model development, monitoring, and validation approaches meet regulatory expectations (e.g., SR 11-7) and internal risk management needs
Evaluate conceptual soundness of model specifications; reasonableness of assumptions and reliability of inputs; completeness of testing; robustness of numerical aspects; suitability of performance metrics and risk measures
Review model documents, conduct test runs on model codes
Assess and measure impact of model limitations, parameter estimation, errors, deviations from assumptions; compare outputs with empirical evidence or benchmarks
Document and present observations to Model Validation Team Lead, model owners/users; recommend remediation plans, track progress, evaluate evidence
Monitor model performance reports ongoing to ensure validity; contribute to bank-wide model risk and control assessment
Support development of comprehensive documentation and testing of risk management framework; deliver work requiring little revision
Solve complex quantitative problems, take new perspectives on solutions, act independently using technical experience and judgment
Establish and maintain strong relationships with key stakeholders (model developers, owners, users)