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Walmart Data Scientist Interview Questions

Walmart Data Scientist Interview Questions – We interviewed a couple of folks working as a Data Scientist at Walmart. According to them the interview will be quite technical in nature with a lot of emphasis on ML and Python. SQL questions are also asked(not more than 4-5). You can practice the questions below to get yourself familiar with Walmart Data Scientist Interview Questions

Role – Data Scientist
Location – Gurgaon, India
Interview Year – 2021


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Round 1 – Technical

Topics covered – Coding

Mode of interview – Hackerrank
Duration – 45 Minutes
Level of Questions – Easy
A few questions from this round:

Print all the branches in a binary tree
Join two sorted arrays

Round 2 – Technical Round

Topics covered – probability and statistics and big data questions
Mode of interview – Hangout
Duration – 1 hour
Level of Questions – Medium
What is the difference between Gradient Boosting and Random Forest?
What are the different types of Sampling methods that you have used?
Explain the difference between bagged and boosting models.
What is cross entropy?
What is multi-collinearity, how do you fix it in a regression?
What is the significance of log odds?
Give some problems or scenarios where map-reduce concept works well  and where it doesn’t work.
Given a dataset having employee id and manager id find the employees who are also managers ?
A person is using search engine to find something, you know nothing about her/him, how do you come up with am algorithm that will predict what she/he needs after the user types only a few letters ?

Round 3- Technical
Topics- Machine learning
Mode of Interview- Hangout
Duration – 1 hour
Level of questions- Medium

A few questions from this round:

Let’s say we want to build a model to predict booking prices on Airbnb. Between linear regression and random forest regression, which model would perform better and why?
 Generally, what happens to bias & variance as we increase the complexity of the model?
What is the intuition behind F1 score?
Describe how you would build a model to predict Uber ETAs after a rider requests a ride.

Round 4 – HR 

Topics covered -Experience
Mode: Telephone Call
Duration – 1 hour
Level of Questions – Mostly on projects

Some questions on past projects, ability to lead a team and previous responsibilities were discussed.
Offer was released in 3-4 days after the Hiring Manager round

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I am the Co-Founder of The Data Monk. I have a total of 6+ years of analytics experience 3+ years at Mu Sigma 2 years at OYO 1 year and counting at The Data Monk I am an active trader and a logically sarcastic idiot :)

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