Describe the single most challenging data science project you led end-to-end in the last 24 months. In 90 seconds, state: the business goal, exact scope (what you owned vs. others), key constraints (data quality, latency/SLA, privacy, headcount), and the measurable outcome with before/after metrics. Then, in a fully digital-first, remote org spanning ≥3 time zones, explain precisely how you aligned Product, Engineering, and Design when their goals conflicted (e.g., Product targets +1.5pp D7 retention, Engineering prioritizes stability/error budget, Marketing demands a rapid reskin). Walk through your decision framework, the artifacts you used (RFCs, PRDs, experiment briefs, decision logs), how you handled disagreement (one concrete “disagree-and-commit” example), your escalation path, and what you institutionalized afterward (playbooks, guardrails, dashboards). Include specific dates, owners, and KPIs you moved, and one mistake you would avoid next time.