Senior Actuarial Analyst - Pricing
Posted Mar 10, 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
Tell me about a rate filing you supported. What did the regulator push back on, and how did you respond?
What they are checking: Whether they have real filing experience and can defend actuarial work clearly to a state regulator.
How do you check your own work before it goes to actuarial leadership?
What they are checking: Whether they have reliable self-review habits, since errors in pricing can affect many policyholders.
What progress have you made on actuarial exams, and how do you balance study with work?
What they are checking: Whether they are committed to the credential path and can manage exam study alongside demanding work.
What would you do
A product manager wants a smaller rate increase than your indication supports. How do you handle that conversation?
What they are checking: Whether they can explain the risk of underpricing while respecting that business decisions involve more than the indication.
Your loss ratio in one state suddenly worsens. How would you investigate the cause?
What they are checking: Whether they break down results by coverage, segment and frequency versus severity before drawing conclusions.
How would you explain a rate change to someone without an actuarial background?
What they are checking: Whether they can make actuarial results clear to product managers and leaders who make decisions.
About the work
Walk me through how you'd produce a rate level indication for an auto line.
What they are checking: Whether they know the steps like on-leveling premium, loss development and trend, which the posting expects.
How do you choose loss trend and development factors when the data is noisy?
What they are checking: Whether they use judgment and multiple methods rather than mechanically accepting whatever the data shows.
How do you work with data scientists on predictive models used in pricing?
What they are checking: Whether they understand GLMs or similar models well enough to collaborate and question model outputs.
What tools do you use for pricing analysis, like SQL, R, Python or Excel, and how?
What they are checking: Whether they have practical technical skills to handle large policy and claims data efficiently.
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As published by Kemper.