Meta Products & Data Culture Questions
Overview of Meta's product ecosystem (e.g., Facebook, Instagram, Messenger, WhatsApp, Oculus/Reality Labs) and the company's data-driven culture. Covers Meta's product portfolio, business strategy, leadership approach, data governance, analytics practices, experimentation culture (A/B testing), data platform considerations, privacy requirements, and cross-functional decision-making within the organization.
HardTechnical
0 practiced
Propose a governance model for third-party research and internal access to Meta datasets (for academic collaborations and internal data scientists). Include approval workflows, data-sharing agreements, access levels, and auditing requirements to maintain compliance and support innovation.
HardTechnical
0 practiced
A high-profile privacy breach occurred due to misuse of internal data access. As the PM owning data tooling, propose structural changes to data governance, role-based access control (RBAC), logging/monitoring, and incident response to minimize future risk and ensure accountability.
EasyTechnical
0 practiced
Describe Meta’s main product portfolio (Facebook, Instagram, Messenger, WhatsApp, Oculus/Reality Labs). For each product, list: (a) core user value, (b) primary monetization model, and (c) one primary metric you as a PM would track to evaluate success. Keep answers concise but specific (3–4 bullet points per product).
HardTechnical
0 practiced
Design a PM-level plan to detect metric manipulation or gaming across multiple product teams (e.g., teams optimizing vanity metrics). Include detection signals, tooling or dashboards needed, governance steps, and remediation actions for confirmed gaming.
MediumTechnical
0 practiced
Compare centralized versus federated data-governance models for a company that owns multiple apps (Facebook, Instagram, WhatsApp). Discuss pros and cons across data quality, speed of product development, privacy, and cross-product analytics, and recommend which you would pick and why.
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