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1,160 applied scientist interview questions shared by candidates

Some questions that were asked: - Can you perform linear regression when two features are identical? - How would you train a logistic regression model when you have many more 0’s than 1’s in your training set? - What are problems with drop-out regularization and how are they tackled? - Why does L2 regularization work better than L1 regularization? - What are random forests? The interview ended with a programming challenge on a (virtual) whiteboard. It was a hard challenge that I could not solve within the ca. 10 minutes that I was given. Having two people watch what you type of course doesn't help.
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ML Applied Scientist

Interviewed at Amazon

3.5★
Apr 23, 2021

Some questions that were asked: - Can you perform linear regression when two features are identical? - How would you train a logistic regression model when you have many more 0’s than 1’s in your training set? - What are problems with drop-out regularization and how are they tackled? - Why does L2 regularization work better than L1 regularization? - What are random forests? The interview ended with a programming challenge on a (virtual) whiteboard. It was a hard challenge that I could not solve within the ca. 10 minutes that I was given. Having two people watch what you type of course doesn't help.

The coding assessment was an easy problem consisting of using a dictionary. On ML breadth and depth, I was posed with a problem and was asked for a solution, discussing data, modelling and evaluations. Interviewer would stop and ask me to go deep on whatever algorithmic solution I would propose (e.g. talk about attention mechanism in Transformers). The behavioural questions consisted of past situations in my working experience, where I should link what I did to the leadership principles of the company.
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Applied Scientist Intern

Interviewed at Amazon

3.5★
Dec 12, 2025

The coding assessment was an easy problem consisting of using a dictionary. On ML breadth and depth, I was posed with a problem and was asked for a solution, discussing data, modelling and evaluations. Interviewer would stop and ask me to go deep on whatever algorithmic solution I would propose (e.g. talk about attention mechanism in Transformers). The behavioural questions consisted of past situations in my working experience, where I should link what I did to the leadership principles of the company.

Technical rounds were on ML, and previous project experience. It involved basics of transformer, and understanding of each function. ‘If you have a task where order of words/ tokens didn’t matter, how would you train for it?’
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Applied Scientist

Interviewed at Amazon

3.5★
Jan 16, 2026

Technical rounds were on ML, and previous project experience. It involved basics of transformer, and understanding of each function. ‘If you have a task where order of words/ tokens didn’t matter, how would you train for it?’

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