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Explain and test completion-rate gaps

UberMachine Learning Engineer · Technical Screen
EasyMachine Learning EngineerTechnical ScreenMachine Learning

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This question evaluates understanding of causal inference, product-metrics analysis, experimental design, and statistical hypothesis testing (including two-sample t-tests) as applied to operational problems in a marketplace.

In a food delivery marketplace, alcohol-related orders have a lower order completion rate than non-alcohol orders.

Answer the following:

  1. Propose several plausible business or operational reasons for why alcohol orders may have lower completion rates.
  2. Describe what additional data you would inspect to validate those hypotheses.
  3. Suppose the company launches a simple randomized intervention to improve completion. Explain how you would evaluate the effect using a two-sample t-test. Include the null hypothesis, alternative hypothesis, assumptions, the test statistic at a high level, and how you would interpret the result.

You do not need to use a time-area switchback design for this question.