Hi community, I wanted to share my experience for the 2 roles that I interviewed for at Amazon.

SDE Intern:

Timeline:
applied - Jan 31st
OA - Feb 1st week
VO - March 2nd week
Waitlisted - March 3rd week

Interview experience:
My interview was not like the usual ones. After the introductions, the interviewer set the definition of the interview, saying that they will ask only 1 coding question, and we will go over the approach and solution. So I wasn't asked any LP in this one.

The coding question was about printing node values in a certain order, in a Binary Tree. It took me about 40-45 mins to solve it. I got the initial approach in 5 mins, and started talking about how I would go about it, wrote some pseudocode, and explained why, with a dry run. The Interviewer gave an edge case where this would fail, and I immediately got a better approach in my mind. I explained that and wrote the code quickly, and the interviewer went through code and was satisfied. I asked him questions for the last 10 mins.

My prep:
2 weeks of non-stop leetcode grind (Blind75 + some new problems in NeetCode150) and prepping behavioral questions by writing stories that mapped to multiple LPs. Having 4-5 stories mapped to a few LPs each will be fine. I had followed the STAR format as mentioned in Amazon's prep materials.

Data Science Intern:

Timeline:
Applied - not sure, probably Dec-Feb sometime
VO - March 3rd Week
Decision - 3rd day after VO

Interview experience:
I had 2 rounds back to back on the same day. I was interviewing with the team that would hire me. The first round was completely about LP. That's 1hr of LP. The 2nd round covered things about my resume, end-to-end workflow of one of my most complex projects, some ML theory and fundamentals, follow-ups about the project I explained, 3 SQL queries (1 + 2 follow-up), 1 simple coding question, and finally 2 LP questions.

The ML theory was just fundamentals; If you read and study daily, it will help you retain your knowledge. The fun part was the end-to-end project discussion. I was completely involved in explaining things, linking the business aspects and value with technical aspects and value, and how data science helped solve a real-world issue.

My prep:
For SQL, I just practiced SQL 50 on leetcode every day. I already had a good grip on SQL given my previous semester's coursework, so it wasn't a problem. I didn't touch leetcode for DSA and LP because, well, I had already prepped for SDE VO. I read a few books for ML theory, and wrote down notes about my projects (work ex. and personal projects), connected all dots, and wrote deep notes for everything, and read them once a day.

Finally, on the 3rd day after my DS VO, I got an email from a recruiter thanking me for interviewing for both roles, and that the team wanted to move ahead with the DS role. I happily accepted it, as DS was my top choice :)

LP prep materials:
https://assets.aboutamazon.com/d4/9b/6d5662ec4a75961ae78c473e7d03/amazon-leadership-principles-070621-us.pdf
https://igotanoffer.com/blogs/tech/amazon-behavioral-interview

ML prep:
Just a lot of Google searching and reading blogs every day

Feel free to ask me any questions, I'll try to answer them!