How would you determine a loop in a linked list?
Data Scientist Interview Questions
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The technical interview was also a breeze. Again, I just walked though my experience. Explained a couple of models that I built - both regression and machine learning. The guy was super nice but no hard balls.
The confirming interview was actually my favorite. First and foremost, it ending up being a second technical interview. But, I think that is because the interviewer was highly technical. There were a few cultural question - such as, what do you do to keep your skills relevant. But again.. insanely easy interview process.
rate yourself on a scale from 1-10 (1 being worst and 10 being best) on the following skills: python, R, SQL?
online test about stats, A/B testing... Reasonable questions.
3 main questions: 1. write an algorithm to generate the probability of obtaining a random number based on a prior discrete distribution. Was asked all the relevant probability theory questions where applicable. asked to solve with and without using numpy library functions. 2. pick any ML algo of my choice and explain it at depth - decision trees in my case - how I have deployed it in a project before - covered all the conceptual details. 3. write SQL queries to offer discounts to customers that may not retain a premium subscription service - how would you determine who will/will not be a recurring customer?
The old test that i did had a time series based ml problem that needed to be solved.
Que vous a apporté votre dernière expérience professionelle.
What are key LLM parameters ?
Some questions can also be presented in the form of a simple case exercise such as how would you process a dataset for training and how would you decide what model to use. Interviewers at all rounds will always ask follow-up questions to your answers so if you suggest an idea or approach, be sure you are familiar with it. They may also ask you about keywords you wrote on your resume. For example, if you wrote “GANs” somewhere on your resume, don’t be surprised if they ask you to explain GANs to them in detail with a bunch of follow-up questions. Make sure you brush up on fundamentals of ML and statistics Science Case study Describe how you will generate your dataset: how you will select an unbiased sample, deal with class imbalance, consider temporal effects. How will you split into train/val/test? I follow this website: https://mlengineer.io/
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