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Historical candidate account: this article preserves one person’s reported experience. The interview date was not recorded in the original text, and updating this page does not make the account a current hiring process. Names, levels, durations, questions, outcomes, and approximate compensation are as reported, not independently verified or endorsed by the employer. Confirm the current role and assessment with the recruiter.
This account describes Mona’s reported interview for an AWS data scientist role identified as L5.
TLDR
Candidate: Mona
Org: AWS
How it gets started: recruiter reached out on LinkedIn
Job level: L5
Year of Experience: 3 years as a data analyst
Degree: M.S in statistics
Offer: Yes
TC: ~200K USD
Location: Austin, TX
Interview process: 5 weeks
Preparation: 2 months
Has a job: yes
Decide to join: yes
Round 1 HR chat:
Basic questions such as whether willing to relocate to Texas, need H1-B sponsorship, why leaving the current company.
Technical screen round 1:
Several medium-level SQL coding questions need to know window functions such as LAG/LEAD, prepared SQL using SQLPad.
See more questions here: Amazon SQL Interview Coding Questions.
Technical screen round 2:
Resume deep dive. Tell me about your favorite project.
Leadership Principle questions: why amazon? Tell me about a time you disagree with your manager. How did you handle it?
Virtual Onsite:
Round 1: Leadership principle: general
- Tell me about a time you have to make a backup plan for a project deadline;
- Give me an example you solved a problem above and beyond;
- What are your biggest strength and weakness?
Round 2: leadership principle: Bar Raiser
- Questions about some projects on the resume
- Which leadership principles are most relevant to your work, and how have you demonstrated them? (Editorially restated without the original outdated count.)
- Give me an example you invented and simplified a solution for a complicated problem.
Round 3: Data engineering and machine learning
How to design a dashboard for executives (non-technical)?
Basic SQL questions.
How to evaluate a machine learning model, how to determine the importance of a feature.
How do you explain R-Square to non-technical people?
Round 4. Leadership principle: collaboration, cross-functional projects
Tell me about a time you worked on a project that involved more than two teams;
Tell me about a time you made an unpopular decision;
Tell me about a time you worked with non-technical people.
Round 5. Leadership, questions to ask with the hiring manager
Tell me about a time you helped a teammate;
What do you see yourself in 5 years;
Why do you want to join amazon?
Do you have any questions for us?
More sample Amazon leadership principle questions.
Offer
Received the job offer the following week.
Use Amazon’s current Leadership Principles as the primary reference; this historical account does not establish today’s interview format.
Prepare evidence for both analysis and collaboration
For a behavioral example, explain your own responsibility, the decision, competing constraints, what you checked, the outcome you actually observed, and what you learned. Do not invent impact or treat a memorized story as an answer to every principle. For an executive dashboard, identify the decision and define each metric, cutoff, and data limitation before discussing chart design. Explain model evaluation using a baseline and an appropriate held-out set. Consult the employer’s current materials for the role’s present assessment.
Practice one reported prompt, state the data and assumptions, produce a checkable answer, and explain one limitation. Then change a condition and see whether your reasoning still holds. Use this related practice resource for a follow-up; it is separate from the historical interview report.
