Show ownership in ambiguous creator-growth work

Tell me about a time you took end-to-end responsibility for a creator growth problem that was not clearly defined. Select one project and walk through these points: 1) the precise business objective and why it was important; 2) how you structured the problem, chose success measures, and weighed trade-offs (such as creator content volume versus viewer satisfaction); 3) a tough disagreement with a product manager, engineer, or fellow data scientist and how you persuaded others without formal authority; 4) a call you made under uncertainty that later proved incorrect—what early indicators pointed that way and what you would change; 5) how you adjusted for regional differences (for example, content norms or regulatory requirements); 6) how you protected long-term system health (guardrails, holdout groups, or winsorization and abuse controls). Keep the account specific with dates, metrics, and the actions you personally took.

Overview: This question assesses product-focused data science skills such as owning a problem from start to finish, framing the issue and defining success metrics, setting priorities among trade-offs, influencing across functions, handling experiments and uncertainty, adapting to geographic differences, and maintaining long-term system health.