25 Data Analyst Domande di colloquio

Walk me through how you'd investigate a sudden 20% drop in a key business metric.

How do you decide which metrics to track for a new product feature?

Describe the most complex SQL query you've written — what problem was it solving?

How do you handle data that you suspect is wrong but can't verify immediately?

What's your approach to building a dashboard that people will actually use?

Describe a time your analysis changed a business decision.

How do you prioritize your analysis requests when everything is 'urgent'?

What's the difference between a vanity metric and an actionable metric?

How do you communicate a complex analysis to a non-technical audience?

Describe your experience with A/B test analysis — what do you check beyond p-values?

How do you approach cohort analysis for a subscription business?

What's your process for data cleaning before analysis?

How do you build a metrics tree for a business objective?

Describe your experience with Python or R for analysis beyond SQL.

How do you check that a data pipeline is producing correct results?

What's your approach to funnel analysis?

Describe a time you found an insight in data that no one had asked you to look for.

How do you handle stakeholders who want the data to tell a specific story?

What's your experience with data visualization tools — Tableau, Looker, Power BI?

How do you think about statistical significance in a business context?

Describe how you'd segment customers for a targeted campaign.

What's your approach to building a self-serve analytics platform?

How do you document your analyses so they can be reused?

Describe your experience with attribution modeling.

What question would you ask yourself before presenting any analysis?