Analytical Background Questions
The candidate's analytical skills and experience with data driven problem solving, including statistics, data analysis projects, tools and languages used, and examples of insights that influenced product or business decisions. This covers academic projects, internships, or professional analytics work and the end to end approach from hypothesis to measured result.
HardTechnical
0 practiced
You are given messy logs from product, billing, and CRM systems and asked to compute weekly customer lifetime value (LTV) aggregated by acquisition channel for the past two years. Describe data cleaning steps, join keys and deduplication strategy, SQL or Spark pseudocode for LTV computation, and approaches for backfilling and reconciling metrics when sources change.
EasyTechnical
0 practiced
Explain the difference between correlation and causation in a business analytics context. Give an example where a strong correlation could be misleading for decision-making, and outline at least two analytic approaches you would use to move from correlation toward causal inference.
EasyBehavioral
0 practiced
Tell me about a time when your analysis produced an insight that changed a product or business decision. Describe the business question, the dataset and tools you used, the analysis steps from hypothesis to result, how you validated the finding, how you communicated it, and the measurable outcome after the change.
HardTechnical
0 practiced
Compare model interpretability approaches: global explanations (feature importances, partial dependence plots), local explanations (LIME, SHAP, counterfactuals), and inherently-interpretable models (rule lists, GAMs). For a high-stakes healthcare model recommend a suitable combination and justify your choice.
EasyTechnical
0 practiced
Describe why accuracy is not a good metric for imbalanced classification problems. Choose an imbalanced business example (e.g., fraud detection) and justify which metrics (precision, recall, F1, AUC-ROC, AUC-PR) you would pick and why. Explain how you would set an operating threshold.
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