Amazon Data Scientist Interview Questions
23+ questions from real Amazon Data Scientist interviews, reported by candidates.
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hi, I have received amazon online test link after I applied for data scientist positions on their job portal. The email is from "no reply" to complete the 90 mins hackerrank assessment. can anyone tel
Data Science In Amazon
I noticed from the experiences I\'ve read that there\'s no specific focus on data structures and algorithms for that role. Of course, you should know them well, but there aren\'t...
Amazon BIE II (L5)
Interview Location : India Hyderabad, Round 1: was an online assesment on hacker rank , which I thought I failed but somehow made it. Round 2 : was a phone screen with...
Amazon Data Engineering Intern Interview Experience
Hi everyone, I had interviewed at Amazon a couple of months back for data engineer role and I am sharing my experience here. Before that I would like to reiterate...
What to expect for Amazon applied science internship and IBM data science internship OA (2023-2024)?
Amazon applied science is 2 hours and IBM is 1 hour for two questions.
Amazon|BIE|technical phone screen|SQL
ORDERS order_id varchar customer_id int order_datetime timestamp item_id varchar item_price decimal item_quantity int primary key (order_id, item_id) ITEMS item_id varchar(10) item_category varchar(20) primary key (item_id) ADDRESSES customer_id int start_date timestamp end_date timestamp zip_code...
Amazon (L5 BIE)| Phone screen | SQL/Database Questions + Analytical
Question 1: You have first two columns in the below table, how do you display the third column like shown below Table1: dw_run_date\tunits\tRolling_3_day_demand 4/20/2020 0:00\t10\t10 4/21/2020 0:00\t20\t30 4/22/2020 0:00\t30\t60 4/23/2020 0:00\t40\t90 4/24/2020 0:00\t50\t120 4/25/2020 0:00\t60\t150 4/26/2020 0:00\t70\t180 4/27/2020 0:00\t80\t210 4/28/2020 0:00\t90\t240 4/29/2020 0:00\t100\t270 4/30/2020...
Interview Experience | Amazon | Data Scientist II Intern
Masters Candidate, Tier1 College Campus Hiring Role: Data Scientist II Intern Duration of Internship: 6 months Stipend: 1.4 LPM Number of Rounds: 2 Round 1: Standard Coding Test (7 Debugging Questions + 2 Coding Questions +...
Amazon, Business Analyst Interview Experience
Summary: Just got an offer for a Business Analyst role at Amazon and feel super excited! The technical assessments were pretty straightforward. I found the Amazon SQL on LC and buying...
Hey, Has anyone here given their internviews for the Amazon Data Science Internship? I would like to know more about the process and what to expect from these interviews.
Amazon|Telephonic|BA Role - Rejected in 1st round
After a long follow up with Amazon HR team today I took my telephonic interview round 1 for a Business Intelligence role, After my little introduction we jumped into sql...
Hello peeps, So I applied to Amazon(YOE 1.2) via the online portal and almost in a week got an OA which included a modified version of pair of song duration...
Interview Question For Data Science ||Part-1
Introduction: Data science is an interdisciplinary field that mines raw data, analyses it, and comes up with patterns that are used to extract valuable insights from it. Statistics, computer science, machine...
The interview started with a general introduction and then I was given the problem statement to read and then explain the approach. Also, the interviewer asked me the internal implementations for...
Amazon Data Scientist Intern
Firstly, I have applied through the portal last year (2020) October and haven\u2019t received any information about that. My friend joined Amazon as an SDE-1 this year (2021) March and...
Amazon | L4 | Research Analyst | Offer
A little late for the post, so I don\'t remember every detail. I appeared for the same in May\'21-Jun\'21. The process took around 6-8 weeks. Status: 3 YoE (Analytics) Prior exp - Accenture,...
Amazon Sr.BIE telephone screen 1st round
5 mins- ice breaker Talk about yourself other than whats on resume. General questions - Talk about what you do as a BIE your accomplishments walk through some of the dashboards you have worked...
Amazon | Data Scientist | Phone Screen | SQL
Hi folks, just wanna share a few sql questions I had on a recent Amazon Data Scientist phone interview there are 2 tables: STREAMS and TITLES STREAMS table USER_ID TITLE_ID STREAM_TIMESTART STREAM_MINUTES Key for this table is...
Amazon DS II Interview (Tech Screen)
Hi Guys, I have 1 hour technical screen with the Hiring manager at Amazon for Data Scientist II role (Seattle) with AWS team in 2days. If anyone can give me pointers...
Amazon - Data Scientist (Offer)
Hi all, I wanted to make a post about my experience with finally getting into FAANG!!! I am sure some of you have seen my posts on here lately where...
What Amazon Looks for in Data Scientist Interviews
Amazon Data Scientist interviews are calibrated against the level and scope expected of the role. Across 23+ verified candidate reports on LeakCode, the consistent signals interviewers look for: clear problem decomposition before coding, explicit complexity reasoning, structured handling of edge cases, and the ability to articulate trade-offs between two reasonable approaches.
The discriminator between candidates who advance and candidates who do not is rarely the final correctness of the solution. It is the path to the solution: did you ask clarifying questions, did you state your approach before coding, did you handle edge cases without prompting, and did you communicate your reasoning throughout. Reports tagged "no hire" frequently cite a working solution with poor communication; reports tagged "strong hire" cite clear thinking even when the final solution was incomplete.
How To Use This Question Set
Real interview reports are a calibration tool, not a memorization target. Companies update their question pools every 2-4 months; memorizing exact problems risks misleading you when the interviewer uses a variant. The high-leverage use: identify the patterns that appear repeatedly in Amazon Data Scientist reports, practice those patterns on similar (not identical) problems, and use the reports to understand the interviewer's typical follow-up depth.
Filter the questions below by round type, difficulty, and recency. Focus first on reports from the past 6-12 months; older reports may reference questions that have since rotated out of Amazon's pool. Reports tagged with quantified difficulty (e.g., "medium-hard") are higher-signal than reports without difficulty tags.
Round-by-Round Expectations
Amazon Data Scientist loops typically span 4-6 rounds across phone screens and on-site or virtual on-site interviews. The structure varies by company: some run 1 recruiter screen + 1 technical phone + 3-4 on-site rounds; others run 1 recruiter screen + 1 OA + 4-5 on-site rounds. The recruiter screen is logistics and culture-light; the technical phone screen is medium-difficulty coding; the on-site loop covers coding, system design (at L4+ levels), and behavioral rounds.
Each round is designed to surface a specific signal. Coding rounds: correctness, code quality, complexity reasoning, communication. System design rounds: requirements clarification, design judgment, operational thinking. Behavioral rounds: ownership scope, leadership, ambiguity tolerance, conflict navigation. Strong candidates explicitly hit each signal dimension out loud during the round; weak candidates focus only on solving the prompt.
Common Interview Mistakes At This Combination
Reports tagged "no hire" at Amazon Data Scientist commonly cite: jumping into code without clarifying requirements, coding silently for 10+ minutes without verbalizing approach, missing edge cases (empty input, single element, very large input, overflow), and producing a working solution that the candidate cannot explain or refactor when probed. Strong candidates avoid these patterns by following a consistent template: clarify, verbalize approach, code with narration, test with examples.
Behavioral and design rounds have their own failure modes. Behavioral: stories that use "we" instead of "I" diluting individual signal, stories with no quantified outcome, defensiveness when probed about failure. Design: not asking clarifying questions, not stating requirements out loud, designing for a single server when the prompt clearly implies scale, ignoring operational concerns (deployment, monitoring, rollback). These show up in roughly half of Amazon Data Scientist interview retrospectives on LeakCode.
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