Demonstrate Amazon LP with deep follow-ups
Overview
This question evaluates behavioral and leadership competencies for a Data Scientist role, focusing on customer orientation, ownership, accountability for missed deadlines, and responsiveness to negative feedback while requiring quantified impact, scope, dates, and trade-offs.
Amazon
Oct 13, 2025, 9:49 PM
Data Scientist
Onsite
Behavioral & Leadership
0
0
Behavioral STAR Stories for Amazon Data Scientist Onsite
Context
You are preparing for an onsite Behavioral and Leadership interview for a Data Scientist role. Prepare four distinct STAR stories with quantification and clear scope, dates, and impact.
Requirements
Create four separate STAR stories covering:
- Customer Obsession
- Ownership
- Missed Deadline
- Receiving Hard Negative Feedback
For each story:
- Use STAR: Situation, Task, Action, Result.
- Quantify metrics moved (what, by how much), scope, cost, and trade-offs.
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Be ready for follow-ups:
- What metric moved and by how much? What cost or trade-off did you accept?
- Where did you disagree and commit? How did you escalate or de-risk?
- What was your single biggest mistake? What would you do differently next time to prevent recurrence?
- How did you handle ambiguity, pushback from a PM, or conflicting stakeholder goals?
- Provide exact dates, scope, and impact.
- Avoid reusing stories; call out which Leadership Principles also apply, such as Dive Deep or Bias for Action.
Solution
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