Interview
Questions
Walmart: Inventory Decision Science
Independent spoken practice for data-science roles working on retail inventory decisions. Explain objectives, data limitations, model validation and reliable operational use.
Practice these questions directly. An editable copy is yours to change; the original stays unchanged.
Describe a machine learning project you worked on that had significant business impact. What was your approach and what results did you achieve?
Walmart needs to improve product availability without building excessive inventory or increasing operating cost. How would you frame the decision, compare the objectives and constraints, and explain the tradeoffs of your recommendation to operations?
Data quality issues can have significant downstream impacts. Describe a time you identified and resolved a data quality problem. How did you prevent it from recurring?
You are evaluating an inventory model for Walmart, and sales are low in stores that frequently run out of the product. How would you check whether the data reflects demand, decide what evidence is missing, and validate the model before recommending wider use?
Walk me through how you approach model selection for a new problem. What factors do you consider?
Tell me about a time when a model you deployed did not perform as expected in production. How did you diagnose and address the issue?
Tell me about a time when stakeholders disagreed with your analysis or recommendations. How did you handle it?