What is precision and recall? Asked how does densenet and gradient boosting algos work? Asked to code up nn
Data Scientist Interviews
Data Scientist Interview Questions
In a data scientist interview, expect employers to ask questions that assess your data modeling, problem-solving, and programming skills. Be prepared to answer general questions that test your knowledge of statistics and data science. You should also be ready to answer open-ended questions that test your creativity, communication skills, and formal education in data modeling and programming.
Top Data Scientist Interview Questions & How to Answer
Question #1: Which data modeling techniques do you prefer and why?
Question #2: How would you detect bogus Instagram accounts used for scamming consumers?
Question #3: Describe circumstances that require a list, tuple, or set in Python.
54,373 data scientist interview questions shared by candidates
Most challenging situation that you have faced.
Some features in model to predict whether the customer will complete order at this time.
Details about random forest that applied on regression problem.
Two Brain Teaser questions, very basic SQL questions and standard Machine Learning/Data Science questions
Describe about you and why do you want this job.
What do you think cleaning validations does?
Foi perguntado o maior desafio como cientista de dados.
background and some details of take-home some questions are very vague, and really not sure what he want... many questions are open ended for me, bc the take-home is not well-designed from my perspective ... it would be better to ask questions related to statistics or machine learning directly... they don't use any fancy ml techniques, but emphasis the statistics
1 coding question : Write a function for sampling from a multimodal distribution. Your inputs are: Keys (i.e. green, red, blue) Weights (i.e. 2, 3, 5.5) N (number of samples drawn from this distribution ( i.e. n=5) Output : list of n keys: Example n = 5: [blue, blue, blue, red, green] Hint: draw a rv of uniform distribution. Calculate the normalized weights for each key. - Machine Learning question : we have a list of items and how many times each item is purchased (range from 10 to 100000 times). For each user the probability of user buying each item is uniform (same across all users). Let’s say we have an item "A" that has been recommended 10 times, has been purchased 10 times. What is the long term probability of being purchased for this item ?
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