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Walmart Global Tech Data Scientist Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 64 interview experiences · FREE TO READ

3.2 Rounds average
Average Typical difficulty
59.4% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at Walmart Global Tech.

Showing 3 of 64
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Walmart Global Tech

Data Scientist

Analytics · a year ago

Senior Average Positive experience No offer 2 rounds
Interview process
Recruiter call Technical screen Technical screen
Interview formats
Technical Coding Behavioral

Started with a recruiter call. Then had a technical interview with Senior Data Scientists where we talked about my resume projects and past work, specifically the technical details and why I made certain design choices. This round also included an Easy DSA coding problem. The second interview was with people from the team, digging deeper into 1-2 specific projects and another Medium DSA coding test. They also asked general ML questions like about random forests, transformers, xgboost, and attention weights. I answered everything okay and passed both coding tests, but then I didn't hear back for over a month and got rejected two months later.

Confirmed questions2 questions
  • Can you tell me about a Data Science/ML project from your resume and walk me through the design choices you made?
  • Explain the design choices for a Data Science/ML project.
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Walmart Global Tech

Data Scientist Intern

Analytics · a year ago

Intern Easy Positive experience Accept offer 4 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Behavioral Technical Coding

So first I had a screening with the Manager, it was mostly behavioral stuff. Then the next round was technical, they asked me questions on python and my past experiences, teamwork, problem-solving skills, and alignment with the company’s values. Then I had another screening with the Manager that was mostly behavioral. Then the next round was technical with questions on python and past experiences, teamwork, problem-solving skills, and alignment with the company’s values.

Confirmed questions6 questions
  • Can you share an instance of working within a team?
  • Can you tell me about your previous experiences?
  • How do you work in a team?
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Walmart Global Tech

Senior Data Scientist

Analytics · a year ago

Senior Average Neutral experience Accept offer 5 rounds
Interview process
Technical screen Technical screen Technical screen Technical screen Technical screen
Interview formats
Coding Technical System Design

So, there were like 5 rounds, all of them were technical interviews. Each round had a coding question, some ML basics stuff, and a system design question. The coding questions were Leetcode medium difficulty and sometimes they had follow-ups. They asked a lot about logistic regression and tree-based models. For the coding part, there was some dynamic programming and sorting involved.

Confirmed questions1 question
  • Can you tell me how to find the index of the maximum element in an array?

Walmart Global Tech Data Scientist Interview Questions

Quoted word for word from Walmart Global Tech interview reports.

Can you simulate N throws of a biased die without using the numpy library?

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When would a complex neural network model perform like a linear model?

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Can you explain what F1 score is and the reason behind its name?

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Could you explain what cross-entropy is, and please provide the formula?

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Can you explain the difference between a random forest and a gradient boosted tree?

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Can you explain the difference between L1 and L2 norms?

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Can you tell me how to find the index of the maximum element in an array?

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Could you explain type 1 and type 2 errors, and what parameters are necessary for a T-test?

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What metrics can be used for evaluating LLMs when target values are unavailable?

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Formats, difficulty and experience

Across all 64 Walmart Global Tech interview reports.

Interview formats

Technical 40.9%
Coding 27.1%
Behavioral 24.3%
System Design 2.8%
Presentation 2.2%

Interview difficulty

Easy 9.4%
Average 68.8%
Difficult 21.9%

Candidate experience

Neutral 17.2%
Negative 23.4%
Positive 59.4%