Analyze User Transfer Distribution in Initial Launch Period
Overview
This question evaluates proficiency with count-data distributions, summary statistics (mean, median, mode, percentiles), and the impact of adoption and retention dynamics on product metrics, testing statistical modeling and analytical reasoning in the Statistics & Math domain for a Data Scientist role.
Meta
Jul 12, 2025, 6:59 PM
Data Scientist
Onsite
Statistics & Math
19
0
P2P Payments: Transfers per User in the First 30 Days
Scenario
A new peer‑to‑peer (P2P) payments feature has just launched. You are asked to analyze how many transfers users make early on.
Assume a 30‑day calendar window after launch. Clarify your denominator: either (a) all eligible users of the app, or (b) only users who made at least one P2P transfer ("activated" P2P users). State your assumption or answer for both.
Question
- What distribution do you expect for the number of transfers per user in the first 30 days post‑launch? Briefly justify (e.g., right‑skew, long tail, log‑normal/Pareto behavior).
- Estimate where the mean, median, mode, and 95th percentile would lie in that period.
- After two months, how and why would this distribution change?
Hints
- Discuss right‑skew, zero inflation, long tail, and possible log‑normal/Pareto or negative‑binomial behavior.
- Consider adoption, onboarding frictions, network effects, and churn/retention dynamics.
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