Investigate Anomalies in Coinbase Wallet Engagement Metrics

Q: Investigate Anomalies in Coinbase Wallet Engagement Metrics

This question evaluates a data scientist's ability to investigate product wallet metric anomalies by forming falsifiable hypotheses and specifying the exact analytics, feature-flag, backend, acquisition, and on-chain signals that would confirm or refute each hypothesis.

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Question

Coinbase Wallet: Anomaly Investigation Framing

Context

You observe an unexpected spike or drop in a key Coinbase Wallet metric (e.g., DAU, transactions sent, swaps, on-chain success rate). Your job is to quickly form falsifiable hypotheses and outline the exact data signals that would confirm or refute each one.

Assume you can access: product analytics events, app/version/OS info, feature flag/experiment logs, backend API metrics, acquisition/CRM data, on-chain metrics (fees, tx counts, chain health), and incident dashboards.

Task

Propose a concise set of falsifiable hypotheses for a wallet metric anomaly.
For each hypothesis, list the data signals/slices that would confirm or refute it.
Identify the key data slices you would use during triage.

Investigate Anomalies in Coinbase Wallet Engagement Metrics

Coinbase Wallet: Anomaly Investigation Framing

Context

Task

Solution

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