This question evaluates decision-making, ownership, risk assessment, stakeholder management, product impact analysis, and post‑mortem reflection competencies relevant to data scientists.
Describe one specific decision you owned that materially affected users, revenue, or roadmap, and that ultimately proved to be wrong.
Address the following:
(a) Context: the objective, options considered, constraints, stakeholders, and the data available at the time.
(b) Decision framework: trade-offs, risks, expected value (if applicable), why the decision failed; include unknown unknowns and cognitive biases.
(c) Detection and response: the signals that revealed the mistake, how you course-corrected, how you communicated across teams, and the measurable outcomes.
(d) Prevention: if you could redo it, what process changes, safeguards, or alignment mechanisms would you implement to prevent recurrence? What mechanisms have you instituted since?
Keep product details anonymized if needed.
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