Interview
Questions

Describe a machine learning project you worked on that had significant business impact. What was your approach and what results did you achieve?

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?

How have you explained complex technical findings or model limitations to non-technical stakeholders? Give me a specific example.

Describe a time you worked with messy or incomplete data. How did you handle it and what was the outcome?

Tell me about a time when stakeholders disagreed with your analysis or recommendations. How did you handle it?

Walk me through how you approach model selection for a new problem. What factors do you consider?

Describe a project where you had to collaborate closely with engineers, product managers, or other teams. What challenges did you face?

Tell me about a time you had to consider ethical implications of a model or analysis. How did you approach it?

Describe a data science project you delivered under a tight deadline. How did you prioritize and what tradeoffs did you make?

Tell me about a time you had to quickly learn a new technique or technology for a project. How did you approach it?

Give me an example of when your analysis led to a significant change in business strategy or product direction.

Describe a time when you disagreed with a teammate about a technical approach. How did you resolve it?