Expedia Data Scientist Interview Questions + Guide in 2024

Expedia Data Scientist Interview Questions + Guide in 2024

Overview

Expedia Group is a leading global travel platform committed to making travel accessible for everyone. The data scientist position at Expedia involves a blend of coding, data analysis, and collaboration with various departments to drive business insights and improvements.

Are you ready to tackle complex analytical problems and influence positive changes in a fast-paced environment? In this guide, we’ll tackle how they conduct their data science interviews, along with commonly asked Expedia data scientist interview questions to help you prepare better.

What is the Interview Process Like for a Data Scientist Role at Expedia?

Recruiter/Hiring Manager Call Screening

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

In some cases, the Expedia 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.

Online Technical Test

Once you pass the initial screening, Expedia will send you an online assessment focusing on technical skills. This might include coding challenges pertaining to classification problems using datasets like Airbnb.

Technical Virtual Interview

Successfully navigating the recruiter and online test rounds will present you with an invitation for the technical screening round. Technical screening for the Expedia 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:

  • Business understanding and A/B testing
  • Technical questions, including statistics and machine learning scenarios
  • Coding skills with a focus on accuracy

Take-Home Assignment

If you pass the technical interviews, you may be assigned a take-home task. This assignment generally involves analyzing data and presenting your findings. You’ll have a week to complete the task, which tends to include:

  • Performing A/B testing
  • Writing and coding a report based on the data from A/B testing
  • Developing recommendations based on your analysis

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 will be conducted during your day at the Expedia office, including:

  • A 45-minute presentation of your take-home assignment followed by an in-depth discussion on the work you did
  • One-hour interviews focusing on your test, your decisions in the work environment, and your knowledge of data science

Your technical prowess, including programming and ML modeling capabilities, will be evaluated throughout these interviews.

What Questions Are Asked in an Expedia Data Scientist Interview?

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

1. How would you set up an A/B test to optimize button color and position for higher click-through rates?

A team wants to A/B test 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 suspect anything unusual if an A/B test with 20 variants shows one significant result?

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 in a new city?

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

4. What metrics would you use to determine the value of each marketing channel for a B2B analytics company?

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

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

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

Identify the type of model used for determining loan approval based on customer inputs.

13. How would you compare two credit risk models for predicting loan defaults?

Given that personal loans are paid in monthly installments, describe how you would measure the difference between two credit risk models over a specific timeframe.

14. What metrics would you track to measure the success of a new credit risk model?

List and explain the metrics you would use to evaluate the performance of a new credit risk model.

15. How would you evaluate the suitability of a decision tree for predicting loan repayment?

Describe the criteria and methods you would use to determine if a decision tree algorithm is appropriate for predicting loan repayment.

16. How would you evaluate the performance of a decision tree model before and after deployment?

Explain the steps and metrics you would use to assess the performance of a decision tree model both before deployment and after it is in use.

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

Describe the process by which a random forest algorithm generates its forest and explain the advantages of using random forest over logistic regression.

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

Explain the interpretation of logistic regression coefficients when dealing with categorical and boolean variables.

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

  • Suppose we have 100 raters each rating one ad independently. Calculate the expected number of good ads.
  • Now suppose we have 1 rater rating 100 ads. Calculate the expected number of good ads.
  • Suppose we have 1 ad rated as bad. Determine the probability that the rater was lazy.

20. How to simulate coin tosses with a given probability of heads?

Write a function that takes the number of tosses and the probability of heads as input. The function should return a list of randomly generated results (‘H’ for heads and ’T’ for tails) equal in length to the number of tosses.

21. How to calculate the sample variance of a list of integers?

Write a function that takes a list of integers as input and outputs the sample variance, rounded to 2 decimal places.

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

  • Calculate the probability of rolling at least one 3 with 2 dice.
  • Calculate the probability of rolling at least one 3 given (N) dice.

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

Given the probabilities that a specific item X is available at warehouse A (0.6) and warehouse B (0.8), calculate the probability that the item X would be found on Amazon’s website.

How to Prepare for a Data Scientist Interview at Expedia

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 Expedia data scientist interview include:

  • Understand A/B Testing: Be sure you can explain how to conduct A/B testing and how to measure if your test group is performing better than the control group.
  • Business Understanding: Many questions will be centered around your business understanding. Reflect on previous projects where you had to make data-driven decisions.
  • Prepare for Behavioral Interview Questions: Be ready to discuss how you manage priorities and communicate complex concepts to both technical and non-technical partners.

FAQs

What is the average salary for a Data Scientist at Expedia, Inc.?

$115,450

Average Base Salary

$131,588

Average Total Compensation

Min: $70K
Max: $163K
Base Salary
Median: $110K
Mean (Average): $115K
Data points: 90
Min: $15K
Max: $246K
Total Compensation
Median: $136K
Mean (Average): $132K
Data points: 27

View the full Data Scientist at Expedia, Inc. salary guide

What is the company culture like at Expedia Group?

Expedia Group fosters an inclusive, diverse, and innovative work environment. The company values creativity and collaboration and provides flexibility in working arrangements. They strive to make a positive impact and are committed to employee growth and a strong support system.

How can I prepare for the take-home assignment for the Data Scientist role at Expedia?

To prepare for the take-home assignment, focus on refining your data analysis and presentation skills. Make sure to understand the business context and be ready to discuss your approach and findings during the presentation. Practicing similar tasks on Interview Query can help build the necessary skills.

What are some common responsibilities for a Data Scientist at Expedia?

Responsibilities include applying knowledge in SQL, Python, or R to solve business problems, optimizing processes, and communicating complex analytical concepts clearly. Data Scientists collaborate with cross-functional teams to derive actionable insights and support marketing and capital allocation decisions.

The Bottom Line

The role of a Data Scientist at Expedia, Inc. offers a unique blend of technical challenges and business impact. You will get the opportunity to delve into A/B testing, statistical modeling, and data-driven decision-making while collaborating with a variety of teams across the organization. The interview process, although rigorous, is designed to be efficient and supportive, reflecting the company’s commitment to a positive candidate experience.

If you want more insights about the company, check out our main Expedia 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 data analyst to learn more about Expedia’s interview process for different positions.

Good luck with your interview!