I won't give details about the question as I respect the confidentiality of the interview. However, to give a general feeling, I think it doesn't hurt to mention the following. For example, code a class that implements a very popular ML algorithm. Even if the algorithm is very simple there are lots of possible improvements and generalisations, how to make it robust, efficient etc. Same thing for a class storing common data formats: dataframe, time-series, etc... how would you efficiently code access methods and/or storing according to the features of these data types?
Machine Learning Scientist Interview Questions
510 machine learning scientist interview questions shared by candidates
How do deploy machine learning algorithm such that the algorithm is still private
Joins & Unions, Filtering & Sorting, Aggregate Functions, Sub queries, String and Date functions,Window functions
1) SQL Questions 2)Python (programs) 3)Aptitude 4)Stats 5) Machine Learning
Python basics, SQL basic questions
For the 1 hour technical interview afterwards, it was questions to get to know me and what kind of algorithms I'm familiar with and other questions like 'what is your favourite machine learning algorithm', 'what are of ML are you interested in? Give an example of something interesting in that area' They never spoke about or asked me anything about my solution to the take home challenge during this interview. They said they were looking for a candidate that will bring something new to the team.
leetcode hard coding problem
map reduce questions, dynamic programming, arrays
Recursion
After you have decided which features to use, describe the process of constructing feature-vectors
Viewing 21 - 30 interview questions