The Home Depot Data Scientist Interview Questions + Guide in 2024

The Home Depot is the world’s largest home improvement retailer with a strong reputation for innovative solutions that enhance the customer experience. With over 2,300 stores across North America, The Home Depot is a leader in the industry, committed to delivering value and convenience to its customers.

In this guide, Interview Query will walk you through the Data Scientist interview process, including common Home Depot data scientist interview questions and valuable preparation tips to help you succeed. Let’s get started!

The interview process usually depends on the role and seniority, however, you can expect the following on a Home Depot data scientist interview:

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from The Home Depot Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, The Home Depot Data Scientist hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for The Home Depot Data Scientist role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around data systems, ETL pipelines, and SQL queries.

In the case of Data Scientist roles, on-site assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at The Home Depot office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Data Scientist role at The Home Depot.

Typically, interviews at Home Depot vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

1. What would you do if friend requests are down 10% on Facebook?

A product manager at Facebook informs you that friend requests have decreased by 10%. How would you approach investigating and addressing this issue?

2. How would you set up an A/B test for changes in a sign-up funnel?

A team wants to A/B test various changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

3. What metrics would you use to determine the value of each marketing channel?

Given all the different marketing channels and their respective marketing costs at a company called Mode, which sells B2B analytics dashboards, what metrics would you use to assess the value of each channel?

4. How would you measure the success of a banner ad strategy for an online media company?

An online media company wants to experiment with adding web banners into the middle of its reading content to monetize effectively. How would you measure the success of this banner ad strategy?

5. How would you investigate a drop in posts per user on Facebook?

The posting tool on Facebook composer drops from 3% posts per user last month to 2.5% posts per user today. How would you investigate this decline? If the drop is specifically in photo posts, what additional steps would you take?

6. Create a function recurring_char to find the first recurring character in a string.

Given a string, write a function recurring_char to find its first recurring character. Return None if there is no recurring character. Treat upper and lower case letters as distinct characters. Assume the input string includes no spaces.

7. Write a query to get the average order value by gender.

Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. Round your answer to two decimal places. Consider only users who have ever placed an order.

8. Identify first-time and repeat purchases by product category.

Analyze a user’s purchases to identify which purchases represent the first time the user has bought a product from its category and which represent repeat purchases. Output a table including every purchase with a boolean column indicating if the user has previously purchased from that category. Sort results by purchase time in ascending order.

9. Parse the most frequent words used in poems.

Given a list of strings called sentences, return a dictionary of word frequencies in the poem. Keys should be the number of times a word is used, with values being lists of words with that frequency. Process all words as lowercase and ignore punctuation.

10. Write a SQL query to select the 2nd highest salary in the engineering department.

Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, select the next highest salary.

11. How does random forest generate the forest and why use it over logistic regression?

Explain how random forest generates multiple decision trees and combines their results. Discuss the advantages of random forest over logistic regression, such as handling non-linear data and reducing overfitting.

12. How would you justify using a neural network model and explain its predictions to non-technical stakeholders?

Describe the business problem and the benefits of using a neural network. Explain the complexity and how you would simplify the model’s predictions for non-technical stakeholders.

13. How would you interpret coefficients of logistic regression for categorical and boolean variables?

Explain how to interpret the coefficients of logistic regression, focusing on the meaning of coefficients for categorical and boolean variables.

14. Which model would perform better for predicting Airbnb booking prices: linear regression or random forest regression?

Compare linear regression and random forest regression in terms of handling non-linear relationships, feature interactions, and prediction accuracy for Airbnb booking prices.

15. What are the assumptions of linear regression?

List and explain the key assumptions of linear regression, such as linearity, independence, homoscedasticity, and normality of residuals.

16. What are time series models and why are they needed over simpler regression models?

Explain what time series models are and discuss why they are necessary compared to less complicated regression models.

17. How would you determine if the difference between this month and the previous month is significant in a time series dataset?

Given a time series dataset grouped monthly for the past five years, describe the method to assess if the difference between this month and the previous month is statistically significant.

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Home Depot data scientist interview include:

• Understand The Home Depot’s Business: Be familiar with The Home Depot’s services, product offerings, and key business units. Understanding the company’s market and data needs can give you a strategic advantage in your responses.
• Showcase Your Business Insight: The Home Depot’s Data Scientist role requires you to leverage data science for business profitability. Highlight your ability to extract meaningful business insights and solve real-world problems through data analysis.
• Practice Effective Communication: The ability to explain complex data-driven insights to non-technical audiences is crucial. Practice presenting your findings clearly and concisely, ensuring you can effectively communicate the impact of your recommendations.

What is the average salary for a Data Scientist at The Home Depot?

What are the key responsibilities of a Data Scientist at The Home Depot?

Key responsibilities include designing and developing algorithms and models, leading and participating in data analytics projects, communicating insights and recommendations to business leaders, collaborating with internal customers and cross-functional teams, and continuously improving data science practices.

What qualifications are necessary for a Data Scientist role at The Home Depot?

Essential qualifications include a bachelor’s degree (or equivalent experience) in a related field, expertise in predictive modeling, data mining, and data analysis, proficiency in modern scripting languages like Python, experience with data visualization tools such as Tableau, and strong statistical analysis skills. Preferred qualifications include a master’s degree, 4+ years of experience in business intelligence and analytics, and proficiency in SQL and Google BigQuery.

What is unique about The Home Depot’s data science team?

The Home Depot’s data science team focuses on leveraging data science as a competitive edge to drive business success. They work on projects involving optimization, computer vision, recommendation, search, and NLP, among other specializations. Team members are encouraged to stay updated on the latest advancements and contribute to building a robust internal knowledge base.

The Home Depot offers a Data Scientist position that is integral to driving business profitability, efficiency, and customer experience improvements. With responsibilities ranging from advanced analytics methodology application to effective communication with business leaders, this role leverages data science as a competitive advantage. If you’re ready to help shape the future of one of the nation’s largest home improvement retailers, this role presents a unique opportunity to influence significant business decisions and outcomes.

If you want more insights about the company, check out our main Home Depot Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about The Home Depot’s interview process for different positions.

Good luck with your interview!