Model Validation Analyst validating mathematical models in the banking sector. Engaging with internal and external teams to assess model accuracy and compliance.
Responsibilities
Perform validation of all models deemed in-scope by the bank-wide Model Risk Policy.
Develop independent benchmarks for use in the validation of models.
Assess the appropriateness, reasonableness of model assumptions, and accuracy of model implementation.
Prepare detailed reports describing the mathematical analytics of the model, validation techniques employed, test results obtained, and any model limitations noted.
Prepare Management summaries highlighting the outcome of the validation process for each model and outlining recommendations for approval or further improvements.
Establish and maintain productive working relations with internal model development groups and external vendors.
Identify the need to implement new models/techniques for risk management as industry standards evolve and regulatory requirements change.
Requirements
Strong statistical background and excellent analytical and problem solving skills with a graduate degree in one or more of the following areas: statistics, economics, finance, mathematics, computer science and engineering.
3-5 years of experience with model development/validation, including machine learning models, dealing with PPNR stress testing, scorecard and/or capital models
Hands-on experience with relevant programming languages, such as Python, SAS, R is a must
Knowledge in retail banking products, customer behaviours, and macroeconomic impacts is a definite asset
Excellent verbal and written communication skills
Good time management and multitasking skills
Quick learner who grasps new concepts and techniques quickly
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