eBay Data Analyst Interview Questions + Guide in 2024

eBay is a global leader in e-commerce, connecting millions of buyers and sellers worldwide. Known for fostering innovation, eBay’s inclusive culture aims to shape the future of global commerce.

This guide will walk you through the interview process, along with sample eBay data analyst interview questions, detailing key areas to prepare for based on real candidate experiences. Lets get started!

The interview process usually depends on the role and seniority, however, you can expect the following on a eBay data analyst interview:

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the eBay 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 eBay data analyst 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 eBay data analyst role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around eBay’s data systems, ETL pipelines, and SQL queries.

In the case of data analyst roles, take-home 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 eBay 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 analyst role at eBay.

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

1. How would you set up an A/B test for button color and position changes?

A team wants to A/B test multiple 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 set up this test?

2. Would you trust the results of an A/B test with 20 variants if one is significant?

Your manager ran an A/B test with 20 different variants and found one significant result. Would you find anything suspicious about these results?

3. Why might the average number of comments per user decrease despite user growth?

A social media company sees a slow decrease in the average number of comments per user from January to March in a new city, despite consistent user growth. What could be the reasons, and what metrics would you investigate?

4. What metrics would you use to determine the value of marketing channels for Mode?

Given all the different marketing channels and their respective costs for Mode, a company selling B2B analytics dashboards, what metrics would you use to determine the value of each marketing channel?

5. How would you locate a mouse in a 4x4 grid using the fewest scans?

You have a 4x4 grid with a mouse trapped in one cell. You can “scan” subsets of cells to know if the mouse is within that subset. How would you figure out the mouse’s location using the fewest number of scans?

6. Create a function find_bigrams to return a list of all bigrams in a sentence.

Write a function called find_bigrams that takes a sentence or paragraph of strings and returns a list of all its bigrams in order. A bigram is a pair of consecutive words.

7. Write a query to get the last transaction for each day from a table of bank transactions.

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

8. Create a function find_change to find the minimum number of coins for a given amount.

Write a function find_change to find the minimum number of coins that make up the given amount of change cents. Assume we only have coins of value 1, 5, 10, and 25 cents.

9. Design a function to simulate drawing balls from a jar.

Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

10. Create a function calculate_rmse to compute the root mean squared error.

Write a function calculate_rmse to calculate the root mean squared error of a regression model. The function should take in two lists, one representing the predictions y_pred and another with the target values y_true.

11. What’s the difference between Lasso and Ridge Regression?

Explain the key differences between Lasso and Ridge Regression, focusing on their regularization techniques and how they handle coefficients.

12. What kind of model did the co-worker develop for loan approval?

Your co-worker developed a model that takes customer inputs to decide loan approval. Identify the type of model and explain how you would compare it with another model predicting loan defaults, considering monthly installments. Also, the metrics must be specified to track the new model’s success.

13. How would you evaluate and deploy a decision tree model for loan repayment prediction?

As a data scientist at a bank, you need to build a decision tree model to predict loan repayment. Describe how you would determine if a decision tree is appropriate and how you would evaluate its performance before and after deployment.

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

Explain the process of how a random forest generates its forest of trees. Additionally, discuss the advantages of using random forest over logistic regression.

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

Describe the method to interpret logistic regression coefficients, specifically for categorical and boolean variables.

16. What is the expected number of good ads rated by different types of raters?

1. Suppose we have 100 raters, each rating one ad independently. What’s the expected number of good ads?
2. Now suppose we have 1 rater rating 100 ads. What’s the expected number of good ads?
3. Suppose we have 1 ad, rated as bad. What’s the probability the rater was lazy?

17. Write a function to simulate coin tosses with a given probability of heads.

Create a function that takes the number of tosses and the probability of heads as input and returns a list of randomly generated results (‘H’ for heads, ’T’ for tails).

Example 1:

tosses = 5
probability_of_heads = 0.6

Output:

coin_toss(tosses, probability_of_heads) -> ['H', 'T', 'H', 'H', 'T']

Example 2:

tosses = 3
probability_of_heads = 0.2

Output:

coin_toss(tosses, probability_of_heads) -> ['T', 'T', 'T']

18. Write a function to calculate the sample variance of a list of integers.

Create a function that takes a list of integers and returns the sample variance, rounded to 2 decimal places.

Example:

test_list = [6, 7, 3, 9, 10, 15]

Output:

get_variance(test_list) -> 13.89

19. What is the probability of rolling at least one 3 with dice?

1. What’s the probability of rolling at least one 3 with 2 dice?
2. What’s the probability of rolling at least one 3 given (N) dice?

20. What is the probability of finding an item on Amazon’s website given its availability in warehouses?

Given that the probability of item X being available at warehouse A is 0.6 and at warehouse B is 0.8, what is the probability that item X would be found on Amazon’s website?

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 eBay data analyst interview include:

• Brush Up On Technical Skills: Ensure you are proficient in SQL, Excel, and data visualization tools. Practice SQL queries that use complex joins and aggregation functions. Revisit statistical methods and machine learning concepts.
• Prepare for Case Studies: You might be given business scenarios or case studies focusing on data analysis and real-world applications. Work on concise yet comprehensive solutions.
• Know eBay’s Products and Services: Understanding eBay’s ecosystem, including their data-centric operations and challenges, will give you an edge. Be ready to discuss how your skills can contribute to their existing processes.

What is the average salary for a Data Analyst at Ebay?

What skills are essential for a Data Analyst role at eBay?

Key skills include proficiency in SQL and advanced Excel, strong analytical and problem-solving abilities, and familiarity with visualization tools like Tableau. Additionally, having experience with Python, data warehouse architectures, and a strong ability to derive and communicate insights concisely are highly valuable.

What is the company culture like at eBay?

eBay prides itself on being an inclusive and purpose-driven community. The company fosters an environment of creativity, collaboration, and diversity. Employees are encouraged to bring their unique perspectives and ideas to the table, ensuring a rich and supportive workplace.

As the world of e-commerce continues to evolve, eBay is on the lookout for data analysts who are inspired by passion, courage, and creativity. By putting your best analytical foot forward—through targeted SQL knowledge, problem-solving skills, and proficiency in tools like Python and Tableau—you’ll stand out from the competition and ace that interview.

If you want more insights about the company, check out our main eBay Interview Guide, where we have covered many interview questions that could be asked. Additionally, explore our interview guides for other roles such as software engineer and business analyst to learn more about eBay’s interview process for different positions.

Good luck with your interview!