Hopper Software Engineer Interview Questions + Guide in 2024

Hopper aims to create the most customer-centric travel company, leveraging massive amounts of data and machine learning to build a fast-growing mobile-first travel marketplace. Since launching, Hopper has evolved into a global travel fintech provider, powering major travel brands and servicing millions of users.

Joining Hopper as a Software Engineer provides an exciting opportunity to impact the future of travel selling and booking technology. You will be responsible for crafting, implementing, and deploying sophisticated backend systems that enhance Hopper’s award-winning user experience. This role entails working closely with cross-functional teams, solving challenging technical problems, and contributing to a dynamic, innovative environment.

If you’re ready to join a leading force in travel technology, this guide will walk you through the interview process, commonly asked Hopper software engineer interview questions, and helpful tips. Let’s get started!

The interview process usually depends on the role and seniority; however, you can expect the following on a Hopper software engineer interview:

Recruiter/Hiring Manager Call Screening

If your CV is among the shortlisted few, a recruiter from Hopper’s 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.

Sometimes, the Hopper hiring manager might be present during the screening round to answer your queries about the role and the company itself. They may also engage in surface-level technical and behavioral discussions.

This whole recruiter call usually takes about 30 minutes.

Technical Online Assessment

Successfully navigating the recruiter round will invite you to the technical screening round. This technical screen consists of an online programming assessment that must be completed within a given timeframe. Typically, the questions focus on algorithms and data structures. Practice your skills on Interview Query to enhance your chances of success.

Technical Virtual Interview

If you pass the online assessment, you will advance to a virtual technical interview with a developer from the team you are applying to. This interview, conducted over video conference and screen sharing, lasts around one hour. The questions will usually be technical, often resembling “leet code style” problems combined with some follow-up modifications.

Onsite Interview Rounds

You may be invited to an onsite interview loop following the technical virtual interview. This will typically include several sessions:

1. Culture Fit Interview - Focus on Hopper’s values and how you align with them.
2. Product Philosophy Interview - Explore your understanding of product development and problem-solving approaches.
3. Technical Interviews—Usually, there will be two technical rounds to assess your skills in algorithms, data structures, and system design.
4. Bar Raiser Interview - A final session focusing on behavioral aspects.

Behavioral Round

You will undergo a behavioral round with a hiring manager toward the end of your onsite loops. Expect questions about your previous experiences, challenges you’ve faced, and your approach to problem-solving. Answers should ideally follow the STAR (Situation, Task, Action, Result) format.

Typically, interviews at Hopper vary by role and team, but common software engineer interviews follow a fairly standardized process across these question topics.

1. How would you improve the search feature for activities in San Francisco on the Facebook app?

We want to enhance the search results for users looking for things to do in San Francisco. What would you investigate, and what metrics would you use to evaluate the current search functionality’s performance?

2. 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.

3. 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 used.

4. How would you compare two credit risk models for predicting loan defaults? What metrics would you track to measure the success of a new credit risk model?

Since personal loans are monthly installments, describe how you would measure the difference between the two credit risk models over time.

Identify the key metrics you would use to evaluate the success of a new model predicting loan defaults.

5. How would you evaluate if a decision tree is the correct model for predicting loan repayment? How would you evaluate its performance before and after deployment?

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

Explain the steps and metrics you would use to assess its performance before and after deployment.

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

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

7. 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.

8. 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?

9. How would you 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 and returns a list of randomly generated results (‘H’ for heads, ’T’ for tails) equal in length to the number of tosses.

10. How would you calculate the sample variance of a list of integers?

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

11. 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?

12. 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?

13. 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.

14. 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.

15. 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.

16. 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.

17. Develop a function calculate_rmse to compute the root mean squared error.

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

Here are some tips on how you can effectively prepare for a Hopper software engineer interview:

1. Know Your CS Fundamentals: Hopper interview questions are standardized and heavily focused on data structures and algorithms. Study and practice problems on Interview Query to strengthen these areas.

2. Understand System Design Basics: Be prepared for a system design round where you must demonstrate your ability to craft scalable and efficient systems. Practice designing real-world solutions that consider trade-offs and optimizations.

3. Showcase Cultural Fit: Hopper values innovation, customer obsession, and leadership qualities. Prepare to discuss experiences and scenarios where you exhibited these traits.

What is the average salary for a Software Engineer at Hopper?

What skills are vital for a software engineer at Hopper?

Key skills include strong backend development, proficiency in Scala or other JVM languages, experience with cloud platforms like Google Cloud, and an understanding of system architecture. Familiarity with service communication methods and infrastructure deployment tools like Terraform is also important.

What is the company culture like at Hopper?

Hopper promotes a culture of entrepreneurship, open communication, and risk-taking. The company values pushing limits and innovation, focusing on customer satisfaction and system quality. Employees enjoy unlimited PTO, a work-from-home stipend, and engaging in team activities.

Interviewing for a Software Engineer position at Hopper can be a multifaceted experience. It is characterized by a series of technical challenges and interactions that test a candidate’s coding, design, and behavioral skills.

For those eager to excel, Interview Query is an invaluable resource. It offers insights and practice questions tailored to Hopper’s interview process. Whether preparing for a software engineering role or for another position at Hopper, this guide will equip you with the necessary tools to navigate the challenges and make a strong impression.

Good luck with your interview!