How many interview rounds does Walmart have for a Data Scientist and what are the stages?

Walmart reports a four-step process for Data Scientist interviews: a Recruiter Screen, a Technical Screen, and a Virtual Onsite Loop. The Virtual Onsite Loop consists of 3 to 4 interviews focused on Machine Learning, live coding, and behavioral questions. The Technical Screen is described as a decisive round emphasizing coding and fundamental statistics, often run by Karat.

How hard are Walmart Data Scientist interviews and what offer rate should I expect?

For Walmart Data Scientist interviews, candidates most commonly report the difficulty as average. In 42 reported interviews, the offer rate is 9%. That means outcomes vary, but the overall loop is not perceived as uniformly hard.

What topics do Walmart Data Scientists get tested on (SQL, ML, statistics, A/B testing)?

Across reported questions, you should be ready for SQL and data manipulation, including SQL window functions and query optimization, plus live coding with pandas for reshaping, pivoting, and imputing missing values. Expect Machine Learning fundamentals and applied statistical thinking, including cross-entropy, class imbalance, false discovery rates, and Bayesian priors and posteriors. A/B testing and experimentation are also common, including handling interference, metric trade-offs between primary and secondary metrics, and quasi-experimental approaches like difference-in-differences when A/B testing is impossible.

Does Walmart test live coding for Data Scientists, and what kind of coding problems appear?

Yes, the interview loop includes live coding in both the Technical Screen and within the Virtual Onsite Loop. The Technical Screen is described as focusing on coding and fundamental statistics, often conducted by Karat. Example topics from reported questions include writing SQL with window functions, optimizing a slow join query, and using pandas to reshape data and impute missing values.

How much does Walmart pay for a Data Scientist, and what compensation range do candidates report?

Compensation reporting for Walmart Data Scientists spans from $45k to a maximum total of $323,788 in candidate and job-posting reports. Base pay has a minimum reported value of $45,000, and total pay varies by level and location. If you are comparing offers, focus on total compensation and account for level and location differences.

What should I prioritize when preparing for Walmart Data Scientist interviews?

Given the loop structure, prioritize fundamentals that show up early, especially coding plus fundamental statistics for the Technical Screen. Then prepare for ML-focused questions and behavioral questions during the Virtual Onsite Loop, since the onsite is described as 3 to 4 interviews covering those areas. Finally, practice experimentation and measurement thinking, since multiple reported questions cover A/B testing design pitfalls, statistical significance and minimum detectable effect, and metric interpretation trade-offs.

WalmartData Scientist

Updated Jul 30, 2026

Walmart Data Scientist Interview Experiences 2026

Real, anonymous reports from people who interviewed for Data Scientist at Walmart, newest first and distilled into what to expect across the loop.

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Hot & recentNewest first

2 months ago

Difficult Negative Sunnyvale, CA

My interview process felt unusually intense and a bit chaotic from the start. After an initial technical screening phase, I had a supply chain-focused technical round with multiple interviewers at once, including SQL, Python, statistics (one of the questions was probability), and then deeper discussion of machine learning model details. The session ran about 1.5 hours and was heavily oriented toward time series modeling, which ended up being hard to engage with because the interviewer’s accent made it difficult to follow every prompt and nuance.

The round after that didn’t feel more organized either. Across the technical stages, I saw a broad mix of topics tied to resume background, plus hands-on elements like pandas and coding, and then fundamentals spanning decision trees, XGBoost, clustering, probability math, and even references to transformers/BERT and cross-entropy. It was a lot of ground to cover and it felt hard to predict what level of depth would be expected.

4 months ago

Easy Positive Toronto, ON

I started with HR reaching out a few weeks after I applied. The call included basic qualifying questions and my availability, and then I moved into a one-hour technical discussion on Zoom with the hiring manager.

The next step leaned into a coding-style format: a Hackerrank round, followed by a Teams interview with a senior data scientist. Part of that Teams session involved walking through my Hackerrank results and then digging into technical questions, and the other part turned more behavioral. Overall it didn’t feel impossible, though the process felt slightly under-specified until I actually sat down.

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What to expect

Distilled from the reports

Interview Structure & Flow

Candidates reported a lack of organization and clarity throughout the interview process, with rounds blending various topics and formats, leading to unpredictability in expectations and assessments.

UnstructuredConfusingMixed topics

Technical Rounds & Topics

The technical interviews covered a wide range of topics including SQL, Python, statistics, and machine learning, with some candidates feeling unprepared for the depth of knowledge expected, particularly in time series modeling and advanced algorithms.

SQLMachine LearningStatistics

Behavioral & HR Screening

The initial HR screening involved basic qualifying questions, but candidates felt that the behavioral aspects in later rounds were not well integrated or aligned with their technical preparation.

BehavioralHR ScreeningQualifying Questions

Assessment Formats

Candidates experienced various assessment formats, including a Hackerrank coding challenge and a predictive modeling test, but faced issues with timing and clarity regarding expectations for these assessments.

HackerrankPredictive ModelingAssessment Timing

Communication & Follow-Up Issues

Several candidates encountered communication breakdowns, including missed interviews and lack of follow-up from recruiters, contributing to a frustrating overall experience.

CommunicationMissed InterviewsFollow-Up

Timeline & Process Duration

The interview process was reported to be lengthy, with some candidates experiencing delays that led to misalignment between expectations and the final interview content, affecting their overall impression of the process.

Long ProcessDelaysMisalignment