They focus a lot on their leadership principles and your resume
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.
54,300 data scientist interview questions shared by candidates
1- Machine Learning concepts 2- Data Structure Case Study (Very easy) 3- Coding (Easy but they need hands-on exp) And Finally, Leadership (14 principles)
Q: Given a function with inputs --an array with N randomly sorted numbers, and an int K, return output in an array with the K largest numbers. Q: 1. How does GMM/HMM work 2. Name some dimensional reduction method; I said PCA and we talked a bit about how PCA works and what's the physical intuiation 3. How K-means work, what kind of distance metric would you choose, what if different features have different dynamic range 4. How GMM works (EM algorithm)
How to build a summary table out of a written-in-a-notepad-document table of cricket wins and losses by country. How to check the validity of an IP address string given some list of constraints.
Why did you use Random Forests instead of Clustering?
How do you find out trending queries/topics? How do you test a website feature i.e. given a set of webpages and few changes, how will you find out that the change works positively?
En quel animal vous réincarneriez-vous ?
You have a database of customer transactions and for some users you don’t have much data (1-2 transactions), and you want them to use Revolut’s services more. How would you analyse the data to do so, with such limited data on some users.
Model Deployment. Credit Risk(A lot of credit risk concept) Risk Modeling.
Nothing was unexpected
Viewing 501 - 510 interview questions