Pricing Strategy and Insights Sr Analyst, Rosemont, IL
Posted Sep 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 time your analysis changed a commercial decision.
What they are checking: Proof that their analytical work creates measurable business impact, as the posting expects.
Describe a time you had to work out a business problem with no clear direction.
What they are checking: Intellectual curiosity and self-direction, which the posting calls out for this role.
What would you do
A pricing change raised margin but volume dropped. How would you decide whether it was a success?
What they are checking: Whether they weigh total profit, customer retention and long-term effects rather than one metric.
How would you explain a pricing recommendation to field sales leaders who worry about losing customers?
What they are checking: Ability to translate technical findings into clear, credible recommendations for skeptical audiences.
Field pricing teams say a model's recommended prices do not match what they see with customers. How do you respond?
What they are checking: Whether they treat field knowledge as useful signal and investigate rather than defending the model.
About the work
How would you find and size pricing opportunities across thousands of customers and products in foodservice distribution?
What they are checking: Ability to build a quantitative framework that ranks opportunities by size and confidence.
Walk me through how you would design a pricing A/B test when sales reps negotiate prices with customers.
What they are checking: Understanding of the practical limits on randomization in field sales and how to design around them.
When a true A/B test is not possible, what quasi-experimental methods would you use to measure a pricing change?
What they are checking: Familiarity with methods like difference-in-differences and matching, and their assumptions.
How would you estimate how sensitive customers are to price changes in a category?
What they are checking: Understanding of price elasticity and the data problems that make it hard to estimate.
What tools do you use for analysis and modeling, such as SQL, Python or R?
What they are checking: Hands-on depth with the tools needed for advanced analytics on large commercial datasets.
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Practice this out loudThe full job description
As published by US Foods.