VP Model Risk Management
Posted Sep 3, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
You'd deliver management reports on individual and aggregate model risk. How do you express aggregate model risk in a way a management committee can act on?
What they are checking: Whether they can present aggregate model risk clearly to non-technical leaders, so management can make decisions rather than just receive reports.
What would you do
What belongs in an artificial intelligence use policy for a bank right now?
What they are checking: Whether they hold a real, considered view on bank AI use policy, since refining that policy is a stated responsibility of this role.
A model developer disagrees with your validation finding. How do you handle it?
What they are checking: Whether they can defend a validation finding respectfully under pushback, because model risk only works when the second line stays independent.
How do you decide a model should not be used at all?
What they are checking: Whether they have clear criteria and the conviction to stop a model's use, which is the hardest and most consequential call in model risk.
About the work
This role performs validations of all model types used across the bank and helps lead model risk management. Walk me through a validation you ran end to end.
What they are checking: Whether they have owned full validations across model types, because this role is responsible for validation work and helping lead the function.
The posting names ordinary least squares, logistic regression and survival modeling. Take one and tell me what you check hardest when validating it.
What they are checking: Whether they know the named statistical methods deeply enough to validate them, which shows real technical depth rather than general familiarity.
You'd do some validation work directly, programming in Python. What have you built or tested in Python?
What they are checking: Whether they can do hands-on validation work in Python themselves, since the posting explicitly requires coding rather than only supervising analysts.
The posting names following emerging trends in artificial intelligence technology and regulation, and refining validation and use policy. How do you validate a gradient boosting model or a neural network differently from a regression?
What they are checking: Whether they know how validating machine learning models differs from regressions, since that is the harder and growing part of model risk today.
You'd facilitate regulatory examinations and internal audits of the modeling process. How do you prepare for an examination of model governance?
What they are checking: Whether they know how to prepare model governance for a regulatory exam, since facilitating examinations and audits is a named part of this job.
The posting asks for ten to fifteen years in model development or model risk at a midsize or large United States financial institution and a doctorate or master's in a quantitative field, with a hybrid schedule split between remote work and Rosemont. Where do you sit on all of that?
What they are checking: Whether their experience, degree and availability for the hybrid schedule genuinely meet the stated requirements, so both sides can judge the fit.
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As published by Wintrust.