Officer, Model and AI System Risk Management
Posted Aug 28, 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
This role sits in model and artificial intelligence system risk management at the bank's Rosemont headquarters. What model risk work have you done?
What they are checking: Whether they have done real model risk work at the level this officer role requires, rather than adjacent analytics or general risk experience.
What would you do
A business line has been using a spreadsheet to make decisions and does not consider it a model. How do you handle that?
What they are checking: Whether they can identify unrecognized models like spreadsheets and bring them under governance tactfully, since scope gaps are a common model risk weakness.
A model developer disagrees with your finding. How do you handle it?
What they are checking: Whether they can hold an independent finding respectfully under pushback, since model risk only works if the second line keeps its independence.
There is a Vice President role on the same model risk team posted alongside this Officer role. Where do you place yourself, and what would you want to know about the team before you took it?
What they are checking: Whether they place themselves honestly between the officer and VP levels and ask thoughtful questions about the team before accepting either role.
About the work
Walk me through validating a model. What do you check first?
What they are checking: Whether they follow a sound, structured validation method and know what matters most first, which is the core skill in model risk management.
The title names artificial intelligence systems alongside models. What is different about governing an artificial intelligence system compared with a statistical model?
What they are checking: Whether they understand how governing AI systems differs from governing statistical models, since that difference is exactly why this role exists now.
How do you assess a model you cannot fully explain?
What they are checking: Whether they have a practical approach to assessing models they cannot fully explain, which is the central challenge AI brings to model risk.
What belongs in a model inventory, and how do you keep it current?
What they are checking: Whether they know what a model inventory needs and how to keep it current, because every part of a model risk program depends on it.
How do you monitor a model after it goes live, and what makes you escalate?
What they are checking: Whether they monitor live models with clear thresholds for escalation, because models drift after deployment and problems need catching before they cause harm.
What programming do you do yourself, and on what?
What they are checking: Whether they can code and test models hands-on themselves, because this team expects its officers to do technical work, not only review it.
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Practice this out loudThe full job description
As published by Wintrust.