15 questions a Data Scientist interviewer will ask

Tell me about a model you built that had significant business impact. How did you measure it?

How do you handle class imbalance in a classification problem?

Describe a time your analysis contradicted what stakeholders expected. How did you present it?

Walk me through your approach to feature engineering for a tabular dataset.

How would you design an A/B test to measure the impact of a new recommendation algorithm?

Tell me about a time you had to work with messy, incomplete data. What was your approach?

How do you decide between using a simple model vs. a complex one?

Describe how you would build a real-time fraud detection system.

How do you explain a complex model's predictions to a non-technical audience?

Tell me about a project where you had to collaborate with engineers to deploy a model.

What metrics would you use to evaluate a search ranking model?

How do you handle drift in a production ML model?

Describe a time you had to scope a data science project with unclear requirements.

How do you stay current with developments in ML and data science?

Walk me through how you would build a customer churn prediction model.