Chewy Data Scientist Interview Questions + Guide in 2024

Chewy, a leading online retailer for pet products, is known for its dedication to customer service and innovative approach to solving business challenges. The company has quickly become a go-to destination for pet parents looking for quality products and an exceptional shopping experience.

As a Data Scientist at Chewy, you will immerse yourself in a dynamic role that involves building advanced machine learning models, designing data-driven solutions, and engineering pipelines that drive the company’s core objectives. You’ll work on varied tasks, from customer segmentation and fraud detection to supply chain optimization and demand forecasting.

In this guide, we’ll navigate the interview process, common Chewy data scientist interview questions, and valuable tips to help you succeed. Let’s get started with Interview Query!

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

Recruiter/Hiring Manager Call Screening

If your CV is among the shortlisted few, a recruiter from the Chewy Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process. It’s important to remain professional and flexible, as some experiences indicate that scheduling can sometimes be inconsistent.

Sometimes, the hiring manager may also be 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.

Coding Assessment and Technical Interviews

The next step typically involves a combination of coding assessments and technical interviews. Initially, you might be given a coding assessment focusing on Python and SQL to evaluate your data manipulation and analysis skills. Questions may revolve around linear regression models, ETL pipelines, and general Python/SQL queries.

You will likely face a few technical interview rounds following the coding assessment. These interviews will delve deeper into your understanding of machine learning algorithms, data analysis, statistical modeling, and system design. Be prepared to discuss case studies and be evaluated on your problem-solving skills. Presenting previous projects and understanding machine learning concepts like bias-variance tradeoffs and predictive modeling might also be part of this stage.

Final Onsite Interview Rounds

If you successfully navigate the technical rounds, you’ll be invited to attend the final onsite interview (which might also be conducted virtually). This typically includes multiple interview rounds involving presentations, behavioral questions, and in-depth technical discussions to gauge your fit for the team and the company.

Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates. Prepare thoroughly for this stage, encompassing diverse assessment aspects ranging from technical skills to cultural fit.

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

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

Write an SQL query to select the second-highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

2. Create a function to parse the most frequent words in poems.

Create a function to parse the most frequent words in poems. Return a dictionary where keys are the frequency of words and values are lists of words with that frequency. Process all words as lowercase and ignore punctuation.

3. Create a function to find words not common in two sentences.

Create a function that returns a list of words not common in two sentences. Treat words case-insensitively and assume no punctuation or extra spaces.

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

Given all the different marketing channels and their respective costs at Mode, a B2B analytics dashboard company, what metrics would you use to evaluate each channel’s value?

5. How would you measure the success of the banner ad strategy?

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

6. What do you recommend for a $1 million direct mail program investment?

Your team wants to invest $1 million in a direct mail program for the first time. What do you recommend for the short and long term, and how will you measure the direct impact of this investment?

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

Explain how a random forest generates multiple decision trees to form a forest. Additionally, how will you discuss the advantages of using random forest over logistic regression in certain scenarios?

8. Which model performs better for predicting Airbnb booking prices: linear regression or random forest regression?

Consider building a model to predict booking prices on Airbnb. Compare the performance of linear regression and random forest regression, and explain which model would likely perform better and why.

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

Explain how to interpret logistic regression coefficients when dealing with categorical and boolean variables.

10. What is the difference between covariance and correlation? Provide an example.

Describe the difference between covariance and correlation, and provide an example to illustrate the distinction.

11. What are time series models? Why do we need them when we have less complicated regression models?

Explain what time series models are and why they are necessary despite the availability of simpler regression models.

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

Given a time series dataset grouped monthly for the past five years, describe how you would assess whether the difference between this month and the previous month is significant.

13. How would you address a manager’s complaint about a packet filling machine not functioning correctly?

A manager reports that a machine, which is supposed to weigh and pack 25 packets into a box, is malfunctioning. Customers are complaining about incorrect packet counts. How would you investigate and resolve this issue?

To help you succeed in your Chewy data scientist interviews, consider these tips based on interview experiences:

1. Keep Communication Clear and Documented: Given the multiple accounts of communication mishaps, ensure all appointments and interview schedules are well-documented and confirmed via email.

2. Brush Up on Machine Learning and Python: Be proficient in machine learning techniques and Python programming, as these are core to the technical assessments.

3. Be Prepared for Behavioral Questions: Besides technical skills, behavioral questions are significant in the interview process. Be ready to discuss your previous project experiences and how you handle successes and failures.

What is the average salary for a Data Scientist at Chewy?

What qualifications are required for a Data Scientist at Chewy?

Candidates typically need a Bachelor’s degree in a relevant field, such as Computer Science, Engineering, or Mathematics, along with 3 years of experience. A Master’s degree with 1 year of experience is also acceptable. Key skills include Python programming, machine learning techniques, SQL, and experience with data pipeline best practices.

What is the work culture like at Chewy?

Chewy promotes a culture that values creativity, teamwork, and individual growth. Employees are encouraged to think big, thrive on delivering results, and become their best selves. The company also emphasizes inclusivity and values the diverse perspectives of its team members.

If you’re preparing for an interview at Chewy, it’s crucial to arm yourself with detailed knowledge and familiarity with various interview stages and potential questions.

For invaluable resources and insights, check out our main Chewy Interview Guide. We cover many interview questions and offer guides for other roles. At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to tackle every challenge.

You can also explore all our company interview guides for better preparation. If you have any questions, don’t hesitate to reach out.

Good luck with your interview!