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Candidate-reported interview insights

Amino Data Scientist interviews, decoded.

Explore commonly reported questions, interview rounds, difficulty, duration, and candidate experiences for the Data Scientist role at Amino.

3.6 rating Internet & Web Services

Interview overview

Difficulty

Average

Average rounds

3.4

Average duration

~44 days

Difficulty and candidate experience

Interview difficulty

easy0%
average80%
difficult20%

Candidate experience

positive100%

Candidate-reported interview process

I found Amino through a lecture series at Stanford and reached out to their recruiter directly. They responded quickly, and we connected a few days later. The recruiter was great, and the whole interview process was fast, clear, and engaging. I especially liked the 'data science challenge' where I had to code independently to solve some problems before coming in to present my work. They also brought candidates who got offers back to meet their future colleagues, which was a really positive experience and helped me decide to join the company. Overall, it was a great experience.

I was contacted by a really dedicated and informed recruiter. We had a phone screen, and then I got feedback the next day. After that, I had a technical screen with the head of data science. The technical phone screen was about 45 minutes and pretty enjoyable. Later that evening, I had a debrief with the recruiter. Then, I was invited for an onsite interview that lasted 4 hours. Sadly, I was a bit nervous, and it showed, so I didn't get the job. However, they were transparent throughout the process. It was a great interview experience overall, and I really liked the recruiter and the head of data science.

Had a phone screen first, then a full day onsite. We talked about data engineering, machine learning, data product design, and the culture of data science. The technical interviews included whiteboarding and some conceptual questions.

Common Amino Data Scientist interview questions

A focused selection of the most detailed candidate-submitted questions.

  1. 1

    How to rank results from a search query given certain conditions on the computational complexity of the ranking algorithm?

  2. 2

    How would you use the data available and collect additional data on user preferences to serve the best suggestions?

  3. 3

    Describe feature engineering, algorithm design, and evaluation for a given machine learning problem.

  4. 4

    How would you build and grow a DS team with good focus and execution?

Interview question formats

Coding26.7%
Behavioral26.7%
Technical26.7%
Presentation13.3%
System Design6.7%

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Interview information is based on candidate reports and may not represent the current official hiring process of Amino.