Prioritize six improvements for a favorite app
Capital OneData Scientist · OnsiteLast updated
This question evaluates a data scientist's product-thinking, prioritization, impact-estimation, experimentation design, and risk-mitigation competencies, framed within the Behavioral & Leadership domain and focused on product management, modeling, and experimentation.
Choose one consumer mobile app you personally use weekly. 1) Propose exactly six concrete, shippable improvements; for each, specify the target user, the user behavior you aim to change, the primary success metric and a 14-day leading indicator, and the largest execution risk. 2) Build a quick back-of-the-envelope model to estimate each idea’s 90-day impact on the app’s north-star metric; state all assumptions and ranges. 3) Prioritize the six using a transparent framework (e.g., RICE or expected ROI) under the constraint of one squad for one quarter; identify the top priority and justify the trade-offs you accept as CEO (e.g., revenue vs. retention, complexity, brand risk). 4) Define an experiment plan for the top idea: experiment design, go/no-go criteria, guardrail metrics, and explicit kill conditions if early signals underperform. 5) List two non-obvious failure modes and how you would mitigate them pre- and post-launch.
Solution walkthrough is for members
Get the full walkthrough with reference code and complexity analysis, plus Kitty Coach at 300 messages a day. Hints, the code runner and community answers stay free.