I applied through an employee referral. I interviewed at Expedia Group (Ginebra)
Interview
I was asked to start the interview process after someone referred me for the position. The process consisted of the following stages:
1. Basic Data Science: 9 simple questions about machine learning concepts and principles
2. Coding Challenge: 3 coding questions on HackerRank
3. Virtual On-site consisting of a) a behavioral interview b) a data science interview c) live completion of a mini data-science project
Interview questions [1]
Question 1
Data Science Interview (I only remember 8/9 questions):
1. What is cross-validation, where it is used, how do you do it correctly?
2. What are the differences between supervised and unsupervised algorithms?
3. What are examples of structured vs unstructured data?
4. What is multi-collinearity, why is it bad and how do we deal with it?
5. What is data normalization and what are the reasons behind doing it?
6. How would you handle NaNs and outliers?
7. Describe the life-cycle of a data science project
8. What are various evaluation metrics in machine learning and how would you choose between each one of them?
Coding Interview:
1. Print all numbers between 1 and n, omitting multiples of 5 and 7.
2. Variant of the maximum number overlapping intervals problem
3. Write a program to compute the TF-IDF scores of all tokens in a given corpus of documents
Behavioral Interview:
Typical questions that you can find online, nothing unexpected
Data Science Interview
Detailed discussion of my past projects
Mini Data Science Project
I was given some data and asked to explore the dataset and fit a model to predict a certain target on future data points. A simple regression problem. I was given 1,5 hours.
I applied through an employee referral. I interviewed at Expedia Group in Aug 2020
Interview
They used hirevue for technical screening , the interview took about 90 minutes , for two questions you had to record a video and for four questions you had to type your answers, there were time limits to answer all questions but one.
Interview questions [1]
Question 1
questions about past projects and accomplishment, 1 probability question, 1 SQL question, 1 machine learning question about pros and cons of two ML algorithms , 1 feature engineering question related to the team that I was interviewing for.