How I Aced My Walmart Interview on Karat Assessment 2026

Webster Liu

·April 16, 2026

·9 min read

How I Aced My Walmart 2026 Interview on Karat Platform

I recently received an email inviting me to a Karat interview for the Walmart DS (Data Scientist) position. Here is the screenshot:

I still remember the nerves I felt before my walmart Karat experience. I wanted to give myself the best shot, so I took time to really understand the interview format and what the platform expected from me.

To tell the truth, I cheated in my interview with an AI tool called Linkjob.ai without getting caught. It is a useful AI interview assistant that is totally invisible to the Karat OA platform. If you‘d like to know more details, please read my other article about how to cheat on Karat.

I’m really grateful to Linkjob.ai for helping me pass my interview, and that’s also why I’m sharing my entire Walmart OA experience here. Having an undetectable real time AI interview assistant during the interview indeed provides a significant edge.

Dive In Now !

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Key Takeaways

Understand the Karat platform‘s structure. Familiarize yourself with the interview format to reduce surprises.
Practice coding and database skills. Focus on algorithms and SQL queries to excel in technical assessments.
Don’t underestimate behavioral questions. Prepare clear stories that highlight your skills and experiences.
Stay calm during the interview. If you get stuck, don’t hesitate to ask the AI interview assistant for help. It helps you explain your thought process to show your problem-solving skills.
Utilize online resources for preparation. Leverage AI platforms like Linkjob.ai for practice and mock interviews.

Walmart Interview Process on Karat Assessment Overview—Data Scientist/ Software Engineer

Karat OA Platform Basics

Before I started to prepare for my Walmart Karat interview, I wanted to understand how the platform actually works. From my experience, it’s a 60-minute live technical interview conducted through Karat’s system with a remote interviewer.

I was given coding problems in a shared online environment, similar to an IDE, and I had to solve them in real time. The interviewer stayed with me throughout the session and actively interacted—asking follow-up questions, checking my thought process, and sometimes guiding me if I got stuck.

Most of the questions were based on fundamental data structures and algorithms like arrays, strings, and trees. What I realized quickly is that it’s not just about getting the correct answer. I also had to clearly explain my thinking while I was coding, which was just as important as the solution itself.

The interview felt very interactive and time-sensitive. Unlike take-home assignments or traditional coding tests, I couldn’t just focus on finishing first and explaining later. Instead, I had to think out loud, adapt quickly, and respond to feedback in real time.

Karat Assessment Role in Walmart’s Hiring

In Walmart’s hiring process, I saw the Karat interview as a standardized technical screen that determines whether I move on to VO or onsite rounds. It’s essentially pass-or-fail, so that one hour really matters. I was evaluated on coding under pressure, clear communication, handling follow-ups, and staying on track even when I got stuck.

Walmart Interview Format and Structure

From my experience, the Walmart DS hiring process is typically:

HM Screen (Hiring Manager Interview)
Technical Screening
Virtual Onsite (VO)

Coding
System Design / Data Design
Behavioral Interviews

In my case, the process was actually very streamlined:

Karat → directly VO (only 2 hours total)

Much faster than many big tech interview loops

My Recent Walmart DS (Data Scientist) Karat Interview Experience—Real Questions

Self-Introduction

5–6 minute introduction about background, projects, and machine learning experience

Rapid-Fire ML & Technical Questions

For a classification task, is AUROC a good metric for choosing a model? Why or why not?
What are the advantages of using softmax as the last layer in a multi-class classification model?
Suppose you have a linear model with a very large number of features, but only a small portion are useful. Would you choose L1 or L2 regularization? Why?
Given a system where CPU usage remains stable but memory usage keeps increasing over time, what could be the issue?
How would you test whether a service can handle 1000 requests per second (RPS)?

Coding Questions

Given interaction logs:
["Connect/Disconnect", user1, user2]
Output:
- Users with connection count < N
- Users with connection count ≥ N

Given input data:
[user, movie, rating]
Return a list of recommended movies such that:
- The target user has not watched the movie
- At least one other user has watched and rated it > 3
- That user shares at least one commonly liked movie (rating > 3) with the target user

Badge Access Logs Problem

We want to find employees who badged into our secured room together often.
Given an unordered list of names and access times over a single day, find the largest group of people that were in the room together during two or more separate time periods, and the times when they were all present.

Behavioral Questions

Explain the details of a machine learning model used in your project. Why did you choose it?
Describe a time when you identified and implemented an improvement to a process.
Describe a time when you needed to forecast future demand.
What is the part of your past project that you are most proud of?
What challenges did you encountered during project automation, and how did you handle them?

I had practiced these stories before the interview, so I felt ready. I focused on showing collaboration and clear decision-making. I also made sure to connect my experiences to skills that Walmart values, like adaptability and teamwork.

Handling Challenges

When I got stuck in the coding questions, I kept calm, and Linkjob.ai offered me great help without being detected. It not only provided me with the answer, but also outlined the complete reasoning process, allowing me to formulate my response in a more human-like manner.

Linkjob.ai is also invisible to other popular OA platforms. You may click to find out how to ace BCG X CodeSignal assessment.

Undectectable AI Coding Interview Copilot

Tip: If you get stuck, talk through your approach. Interviewers want to see how you think, not just the final answer.

Brief Summary of Walmart Data SWE (Software Engineer) Interview Questions

In addition to the DS (Data Scientist) interview, the SWE (Software Engineer) interview at Walmart also follows a similar Karat-based structure, but with a stronger emphasis on coding and object-oriented design (OOD). The Karat round typically starts with a short introduction, followed by a “pick 2 out of 5” knowledge section. Common topics include OOD concepts such as override vs. overload, polymorphism, and basic testing practices like writing unit tests before deployment.

The coding portion is generally LeetCode easy-to-medium level. Frequently reported problems include variations of string pattern matching (e.g., finding a word that matches a given pattern) and grid-based search problems such as Word Search. In some cases, instead of returning a boolean, candidates are asked to return the coordinates of the matched word in a 2D matrix, which adds a small twist but does not significantly increase difficulty.

Beyond Karat, the Virtual Onsite for SWE usually consists of two rounds. The first round focuses on a deep dive into past projects and includes a system design question, such as designing a system similar to Netflix. The second round is primarily behavioral, led by the hiring manager. Overall, compared to DS interviews, SWE interviews place more weight on coding consistency and foundational engineering concepts, while still maintaining a relatively moderate difficulty level.

Walmart Karat Assessment Interview Preparation Strategies

Researching the Format

When I started preparing, my first goal was just to understand how the Walmart Karat interview actually works. I went through the full process—recruiter screen, Karat technical round, then possible onsite or HM interviews. At the same time, I looked into a detailed analysis of Walmart DS interview patterns and a realistic Karat simulation. That helped me avoid guessing and plan my prep step by step.

Coding and Database Practice

I quickly realized this wasn’t just about LeetCode-style coding. For Walmart DS, SQL shows up a lot, so I had to balance both algorithms and database questions. I used Linkjob.ai’s Walmart DS question bank, which felt surprisingly close to real Karat questions. I practiced writing SQL by hand—joins, aggregations, window functions—and also explained my logic out loud, since that’s a big part of Karat interviews.

If you feel that Walmart DS question bank isn‘t enough for practice, you can also collect real questions from other companies, such as Stripe HackerRank OA questions.

Mock Interviews and Timing

This was probably the most useful part of my prep. I did a lot of timed mock interviews to simulate the real Karat environment. I also used Linkjob.ai’s mock Karat interview mode, which basically mimics the live coding setup and pressure. It helped me get used to thinking while being observed. When I got stuck, I practiced talking through my logic instead of freezing, which made a big difference in confidence.

Note: In addition, Linkjob.ai also offers mock interviews for other OA platforms, including HackerRank and CoderPad.

Success Tips for Walmart Karat Assessment Interview

Do’s and Don’ts

Do’s:
I practiced coding with a timer to improve speed and consistency. I also used AI mock interviews to simulate real Karat conditions. Telling my thought process was essential. I focused on core topics like arrays, strings, SQL, and basic data structures.

Don’ts:
I avoided rushing through answers or staying silent when stuck. Instead, I kept explaining my direction. I also didn’t ignore SQL or behavioral-style questions, since Walmart Karat interviews tend to test more than just coding ability.

Useful Resources

During my preparation, I tried a mix of AI tools, but Linkjob.ai stood out the most. It provided a Walmart DS-focused question bank, realistic Karat-style mock interviews, and a real-time AI interview assistant that helped me practice thinking under pressure in a very interactive way.

Real-time AI Interview Assistant

Mindset Boosters

What helped me most was staying calm and treating each session as practice for real-world problem solving. I relied heavily on AI mock interviews, which made the actual Karat interview feel much more familiar.

I reminded myself that the interview is only 60 minutes, so staying steady matters more than being perfect. I tracked my progress over time and focused on improving step by step instead of expecting instant results.

Note: Consistent practice matters more than last-minute preparation. The more I used realistic simulations, the more natural the real interview felt.

Common Mistakes

Pitfalls to Avoid

Rushing through questions: I sometimes tried to answer too quickly. I learned that taking a moment to plan my approach saved me time in the end.
Not explaining my thought process: I used to solve problems silently. Interviewers want to hear how I think, so I made sure to talk through each step.
Skipping behavioral prep: I focused only on coding at first. Behavioral questions matter just as much. I practiced stories about teamwork and problem-solving.

Recovering from Errors

Mistakes happen, even to the best of us. I learned that how I react matters more than the mistake itself. Here’s what helped me bounce back:

I didn’t panic.
I explained my error and showed how I would fix it.
If I got stuck, I asked the interviewer for a hint.
I kept moving forward, even if I didn’t get everything perfect.

FAQ

How should I introduce myself in the Walmart Karat Assessment interview?

I keep my intro short and focused. I mention my name, background, and one key project that helps highlight skills that match the job. Practicing this 60-second pitch helps me start strong and feel confident.

What if I get stuck on a coding problem?

I talk through my thought process. I explain what I tried and where I got stuck. Sometimes, I ask for a hint. Staying calm and showing my approach matters more than getting the perfect answer.

How do I prepare for behavioral questions?

I write out stories from past experiences and practice reciting them with feeling. This helps me answer clearly and connect my skills to what Walmart values.

Can I use any programming language in the interview?

Yes, I can choose the language I am most comfortable with. I always check with the recruiter before the interview, in order to make sure I know how to write and debug code in that language on the Karat platform.