Q2: What kind of coding language you use in handling large-scale dataset.
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
Question #1: Which data modeling techniques do you prefer and why?
How to answer
How to answer: Turning data into understandable and actionable information is a critical part of the data scientist's job. This question allows employers to understand your data modeling skills and background. List and discuss your preferred data modeling techniques, including benefits such as ease of use, flexibility, etc.
Question 2
Question #2: How would you detect bogus Instagram accounts used for scamming consumers?
How to answer
How to answer: Questions like this one allow an employer to test your problem-solving skills. When answering open-ended questions such as these, feel free to ask clarifying questions and use whiteboards to demonstrate your coding and diagramming skills. Share your thought process as you work through the problem.
Question 3
Question #3: Describe circumstances that require a list, tuple, or set in Python.
How to answer
How to answer: Interviewers will use questions such as this one to test your Python programming skills. Review Python basics such as lists, tuples, and sets before your interview. You should be able to explain when and how each tool is used by data scientists.
54,300 data scientist interview questions shared by candidates
academic-like questions where you could just look up the answer. just memorize a thing or two about the basic algos like neural nets, random forests, svm, linear regression. that satisfies their data scientists.
A project that required several weeks.
What is overfitting and how you deal with it
# Q2: Same as Q1, but now assume there can be duplicates. The output should not have duplicates # Ex: # l1 = [1,2,3,4,5,5,5] # l2 = [1,5,7,11,100] # result = [1,5]
How do you handle conflict?
for the brain games they asked things like what is the fastest route to get out of the box
Easy questions
What’s the probability of observing 1000, given mu = 0 and Sd = 1.
I have a deck and take one card at random. What is the probability you guess it right? Then I give you two questions and you can only ask one: a - is the card red b - is the card 10 spades Which one would you ask and why?
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