Top 30 Walmart Data Analyst Interview Questions + Guide in 2024

Walmart is one of the world’s largest chains of discount department stores. It operates thousands of stores globally, offering a wide range of products at affordable prices.

You can expect competitive salaries, generous incentives such as stock options and their 401(k) match, and a fascinating range of business problems to work on at Walmart. As Walmart focuses on ramping up online sales while continuing to sell products at bargain prices - data analysts are more in demand than ever to help them optimize pricing, operations, and supply chain, build data architecture, and monitor success metrics.

In this interview guide, we’ll help you understand the interview process, take you through the Walmart data analyst interview questions, and share useful tips to land your dream role!

Walmart’s interview process is designed to evaluate your technical knowledge, critical thinking, and cultural fit. This process generally includes:

1. Preliminary Screening: This initial step is conducted by a recruiter to get a sense of a candidate’s background and potential fit. Make sure to use this opportunity to ask the recruiter questions to understand the role, and prepare some key points to sell your skills for the role.
2. Technical Interviews: The screening is followed by a couple of technical rounds conducted over the phone or a video call. You may be asked SQL, Excel, or Tableau questions. Behavioral and case study questions are also often asked in this stage.
3. Onsite Interview: Following successful technical interviews, candidates are invited for onsite interviews, typically with a panel from the team they are expected to join. Here, you’ll face a mix of technical and behavioral interview questions. The team will try to understand how well you’d fit in the given role.

Do remember that while this format is typically followed, the type of questions asked are highly specific to the role and team. We’ve curated below a list of popular analyst questions that you might be asked. Many of these questions have been asked in Walmart interviews, or in similar roles and companies. For more practice, check out our compendium of interview questions.

Walmart data analyst roles typically entail a mix of problem-solving, critical thinking, and tech stack experience in SQL and reporting tools. You also need to have an understanding of machine learning and statistics, be able to code in Python or R, and experience with big data technologies is good to have.

Apart from this, pay attention to the specific role advertised in the job you apply to - is it a product data analyst role? A risk analyst role? A staff data analyst role? The role may require you to build data architecture, analyze user behavior, or even be responsible for information security - so prep for your interview accordingly. For instance, if the job description mentions that you’ll be a part of the transportation analytics team, you may need to understand business operations and solve supply chain case study problems in preparation for the interview.

Our tip: Read the job description thoroughly to understand what your day-to-day role will entail, what tools you will be expected to work on, and what kind of business problems the team is trying to solve. You can leverage these key points to inform your interview strategy. Walmart also has a handy guide on their careers page on acing the interview.

Walmart interviews will consist of at least a few behavioral questions to assess your soft skills, predict your future work, and determine if you’re a team player willing to handle conflict and adapt to changing situations.

1. Why do you want to work with us?

Start with what you admire about the company and how it ties with your personal values and career goals. Demonstrate that you have knowledge about the company, position, and the work that the team does. The interviewer wants to know that you aren’t applying randomly for the role and have an active interest in working for the company.

Tip: Check the Walmart careers page to pick up some pointers for this question. Mirror their language when possible.

2. Tell me about a time you exceeded expectations during a project.

This is your window to impress the interviewer with your work ethic and the relevant skillsets they are looking for. Use the STAR method - discuss the specific situation you were challenged with, the task you decided on, the action you took, and the result of your efforts. Make sure to quantify impact when possible.

Here are a few more behavioral questions for you to get going:

3. What is your approach to resolving conflict?

4. How do you prioritize multiple deadlines?

SQL proficiency is an essential pre-requisite in the Walmart data analyst role, so ensure you practice these questions well ahead of your interview.

5. Write a SQL query to determine if users order more to their primary address versus other addresses.

Given a table of transactions and a table of users, write a query to determine if users tend to order more to their primary address versus other addresses.

6. Write a query that returns all neighborhoods that have 0 users.

We’re given two tables, a users table with demographic information and the neighborhood they live in and a neighborhoods table. Write a query that returns all neighborhoods that have 0 users.

7. Identify which customers placed more than three transactions in 2019 and 2020

Write a query to identify customers who placed more than three transactions each in both 2019 and 2020.

Note: The phrasing of the question institutes this logical expression: Customer transactions> 3 in 2019 AND Customer transactions > 3 in 2020.

8. How would you retrieve the last transaction for each day?

Given a table of bank transactions with columns id, transaction_value, and created_at representing the date and time for each transaction, write a query to get the last transaction for each day. The output should include the ID of the transaction, the datetime of the transaction, and the transaction amount. Order the transactions by datetime.

9. How would you find the cumulative sales amount of each product?

As an accountant for a local grocery store, you have been tasked with calculating the daily sales of each product since their last restocking.

You have been provided with three tables: products, sales, and restocking. The products table contains information about each product, the sales table records the sales transactions, and the restocking table tracks the restocking events. Write a query to retrieve the running total of sales for each product since its last restocking event.

Data analysts at Walmart are often tasked with quantitative analysis, statistical modeling, or sampling work. They are also required to analyze datasets, charts, and model metrics. Having a strong grasp of quantitative skills, particularly in statistics and probability, can help you ace these questions.

11. How would you decrease the margin of error?

Let’s say we have a sample size of n. The margin of error for our sample size is 3. How many more samples would we need to decrease the margin of error to 0.3?

Tip: Ask clarifying questions to better understand the business context, and describe a few key strategies you would employ in this situation. Clearly state any assumptions you make, as any deviation can lead to a larger margin of error.

12. What is a limitation of the R-squared (R^2) method?

Say you are tasked with analyzing how well a model fits the data given. You want to determine a relationship between two variables. What is the downside of only using the R-squared value to do so?

Mention the limitations of the R-squared method while mentioning the instances when you would use it, along with alternative strategies and a few examples.

Here are a few more questions for you to try:

13. Explain the difference between a normal distribution and a binomial distribution. Provide examples of when each distribution might be applicable in a retail context.

14. Walmart is interested in understanding customer satisfaction with a new in-store service. How would you design a survey to gather a representative sample of customers? What sampling techniques would you use, and why?

15. Walmart wants to test if there is a significant difference in customer spending between weekdays and weekends. What statistical test would you use, and how would you interpret the results?

15. How would you retrieve high-value transactions?

You’re given two dataframes: transactions and products. The transactions dataframe contains transaction IDs, product IDs, and the total amount of each product sold. The product dataframe contains product IDs and prices.

Write a function to return a dataframe containing every transaction with a total value of over $100. Include the total value of the transaction as a new column in the dataframe.

16. How would you write a function from a standard normal distribution?

Write a function to get a sample from a standard normal distribution.

Here are a few more Python interview questions that have been asked in Walmart interviews:

17. How would you reconstruct a flight journey?

18. How would you implement k-Means in Python?

19. How would you build a logistic regression model in Python?

20. How would you find the maximal substring?

It is imperative to solve case study questions before your interview. The case study round is your chance to demonstrate your problem-solving ability and your ability to translate your expertise to the common business problems that the Walmart team grapples with. Be detail-oriented, ask clarifying questions, and follow a structured approach in presenting your answer.

21. How would you fix the underpricing of a product on an e-commerce site?

Let’s say you’re a data scientist working on pricing different products on our e-commerce site. The online price is dependent on the availability of the product, the demand, and the logistics cost of providing it to the end consumer.

You discover our algorithm is vastly under-pricing a certain consumer product. What are the steps you take in diagnosing the problem?

Tip: Based on the clarifying questions you ask, clearly present your hypotheses and go through the methodology you would follow to validate each of them. Present a clear solution basis for your investigation.

22. How would you design end-to-end architecture for an e-commerce company?

Let’s say you work for an e-commerce company. Vendors can send products to the company’s warehouse to be listed on the website. Users are able to order any in-stock products and submit returns for refunds if they’re not satisfied. The front end of the website includes a vendor portal that provides sales data in daily, weekly, monthly, quarterly, and yearly intervals.

The company wants to expand worldwide. They put you in charge of designing its end-to-end architecture, so you need to know what significant factors you’ll need to consider. What clarifying questions would you ask? What kind of end-to-end architecture would you design for this company (both for ETL and reporting)?

Here are a few more case study problems for you to try:

23. What metrics would you track in a D2C e-commerce company?

24. How would you determine what products should go on sale to maximize profit during Black Friday?

25. How would you determine the revenue for next year?

Although all data analyst positions do not require machine learning knowledge, it is still a good idea to know the basics of commonly deployed models, especially for prediction and forecasting. We’ve enlisted some questions asked in Walmart interviews below.

26. What are the assumptions of linear regression?

Mention the key assumptions of linear regression, and go through them briefly. Explain in a few brief sentences why it is important to validate these assumptions before building a model and interpreting its results.

27. What is the difference between Bagging and Boosting?

Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? Give an example of the tradeoffs between the two.

Here are a few more common questions on algorithms:

28. Explain how the random forest algorithm works.

29. Regularization vs cross-validation.

30. How would you diagnose an underpricing algorithm?

1. Understand the Company

Research Walmart thoroughly, including its values, mission, recent projects, and challenges in the retail industry. Understanding the company’s culture and goals will allow you to align your responses with what Walmart is looking for in an employee.

2. Tailor Your Resume

Highlight work that is related to the position you are applying to. Look at your CV from the point of view of a prospective interviewer, and edit it accordingly. This will demonstrate early on that you are a good fit.

3. Master Technical and Analytical Skills

Be proficient in SQL, statistics, data analysis tools, and programming languages like Python or R. Practice solving case problems that might come up to showcase your understanding of the role and team. Also, showcase your ability to manipulate and interpret data effectively.

4. Practice Behavioral Questions

Prepare for behavioral questions by recalling past experiences where you demonstrated skills like teamwork, problem-solving, adaptability, and leadership. Use the STAR method (Situation, Task, Action, Result) to structure your answers.

What is the career growth like for a data analyst at Walmart?

With experience, data analysts can advance to senior data analyst roles and managerial positions. Exceptional performers move into manager roles, overseeing teams and developing talent. You may further rise to director-level roles, shaping the company’s overarching data strategy. You could also grow laterally within the organization depending on how you develop your skillsets and where your passion lies, for instance, by leading analytics or product development.

What is the expected salary for a data analyst at Walmart?

The estimated total pay for a data analyst at Walmart is $82,076 per year. The number represents the median, while the range extends from $64,000 to $106,000 per year, according to Glassdoor.

Additional benefits include employee discounts, professional development programs, health coverage, and generous incentives.

Is the Walmart data analyst interview tough?

The analyst role at Walmart is quite coveted, so the interview will assess how well you embody the company values and fit the role. While the difficulty level depends on the type of role and its responsibilities, adequate preparation, an informed interview strategy, and confidence will ensure you sail through the process!

What is the culture like for data analysts at Walmart?

While the culture can vary from team to team, Walmart fosters a dynamic and “customer-first” value system. A good way to find out more about the team’s culture is by asking specific questions at the end of the panel interview.

What software tools do Walmart’s data analysts primarily use?

SQL, Excel, reporting tools like Tableau, Python/R, and big data tools such as Hive or Hadoop are typically used by Walmart analysts. Check the job description to get an idea regarding the tools you’ll be expected to use in your day-to-day.

In conclusion, answering Walmart data analyst interview questions requires technical proficiency, analytical acumen, and effective communication. By understanding Walmart’s unique challenges and culture and practicing sufficient technical and behavioral questions, you can position yourself as an ideal candidate. Remember, strategic preparation, practice, and confidence are your greatest allies!

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