Walk through a DS project end-to-end

Prompt

Describe one data science / analytics project you worked on, end-to-end.

What to cover

Include concise but concrete details on:

• Problem & goal: What business/user problem were you solving? Who were the stakeholders?
• Success metrics: What was the primary metric? What diagnostic and guardrail metrics did you track?
• Data: What data sources did you use? Key tables/events, main features, and major data quality issues.
• Method: What analysis/modeling approach did you choose and why (alternatives considered)?
• Evaluation: How did you validate results (offline metrics, backtests, A/B test, quasi-experiment)?
• Risks & assumptions: Confounders, leakage risk, selection bias, missing data, seasonality.
• Outcome & impact: What changed as a result? Quantify impact if possible.
• Iteration: What would you improve with more time?

Follow-ups (interviewer may ask)

• What was the hardest tradeoff you made?
• What did you do when results contradicted expectations?
• How did you communicate uncertainty and limitations?