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Design and Test a New Feature

UberData Scientist · Onsite
EasyData ScientistOnsiteAnalytics & Experimentation

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This question evaluates a candidate's ability to design a new product feature for a ride-hailing platform and to translate product goals into measurable outcomes, testing competencies in product sense, metric definition, experiment and causal-inference design, segmentation, and two-sided marketplace trade-off analysis.

You are interviewing for a Data Scientist internship at Uber. Assume the Uber rider app already includes standard functionality such as booking a ride, ETA and fare estimates, trip sharing, ride scheduling, and basic safety tools. Propose one genuinely new feature that could improve rider experience and/or marketplace efficiency.

In your answer, explain:

  • the target user and pain point
  • why the feature matters for Uber's business
  • the primary success metric, supporting metrics, and guardrail metrics
  • important tradeoffs, such as rider conversion vs. driver utilization or short-term engagement vs. long-term retention
  • how you would test the feature, including experiment unit, randomization strategy, duration, sample-size or MDE considerations, and how you would handle spillovers in a two-sided marketplace
  • what segments you would examine for heterogeneous effects
  • how you would distinguish true product impact from novelty effects, seasonality, and supply-demand shocks