In a research scientist interview, you'll be expected to show that you have the necessary technical knowledge and expertise pertaining to the specific position you're applying for. Some of the common topics include basic statistical methods, machine learning concepts, and case study analysis. Also, the interviewer will most likely assess your communication and interpersonal skills, which are essential for effective teamwork and funding acquisition.
I have an academic background and I am trying to move to industry. They asked multiple times why I am switching to industry. I also got a lot of non-data science questions, such as basic algorithms questions (sorting, binary trees, time complexity, etc). So it is a good idea to prepare for both. They gave a scenario and ask me to tell a story from my experience that resembles that scenario (these are related to Amazon leadership skills).
I did not get any interview questions. This is just a review for the application process.
How would you build a spam filter for email
1. Which ML model did you use? 2. Explain more details about this model (fundamentals)
Describe an example where you had multiple alternatives to choose from for tools/approaches for a project. How did you go forward?
Leadership questions at a very superficial level.
I'm only remember that I was asked about string manipulations.
Basic data structures questions, implementation of circular queue using array.
Basically questions around the resume. Can go deep in to the details
Generiche, tecniche, machine learning, STAR format, programmazione
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