Booking.com is a leading global online travel agency, known for providing a seamless platform for travelers to discover and book accommodations, flights, and car rentals. It offers vast opportunities for innovation and data-driven decision-making within the travel industry.

As a Data Scientist at Booking.com, you will play a vital role in analyzing and interpreting data to improve user experiences, optimize business processes, and drive company growth. The role demands a robust foundation in statistical analysis, machine learning, and A/B testing, along with the ability to solve complex business problems.

To help you navigate the interview process, Interview Query provides a comprehensive guide, detailing each interview stage, from the initial HR screening to the in-depth technical discussions, ensuring you are well-prepared for each step. Let's dive into the details!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Booking.Com as a Data Scientist. Whether you were contacted by a recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

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

In some cases, the 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 Booking.Com Data Scientist role usually is conducted through virtual means, including video conference and screen sharing. The interview often unfolds in two parts: a detailed discussion about a past project you’ve worked on and a use case primarily revolving around A/B testing techniques and reasoning behind that.

Questions may further delve into topics such as linear regression, bootstrapping, machine learning models, and online experiments. Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

After successfully clearing the virtual interviews, you will be invited to attend the onsite interview loop. The onsite process includes multiple interview rounds, mostly with senior data scientists and business analysts. During these rounds, you will face business cases focused on experimentation, causal inference, and fairly complex data science problems. The interviews are structured to evaluate your problem-solving approach, technical competency, and fit within the company culture.

Occasionally, there may also be a presentation round where you might be asked to present the solutions to the given case studies, especially if take-home assignments were a part of the process.

Quick Tips For Booking.Com Data Scientist Interviews

Here are a few tips to help you excel in your Booking.Com Data Scientist interview:

• Master A/B Testing: Many interviewees have pointed out that a significant portion of the technical interview revolves around A/B testing strategies and insights. Brush up on your knowledge of A/B testing, including hypothesis formulation, result interpretation, and potential pitfalls.
• Project Presentation: Being able to explain your past projects clearly and concisely is crucial. Prepare to discuss your methodology, challenges faced, and the business impact of your work succinctly.
• Be Business-Savvy: Booking.Com evaluates not just your technical skills but also your understanding of business implications. Practice translating technical solutions into business benefits and be ready to discuss how your work drives business value.

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

• - How would you remove duplicate products listed under different names in a large e-commerce database? You are running an e-commerce website and want to eliminate duplicate products listed under different sellers or names. For example, "iPhone X" and "Apple iPhone 10" refer to the same product. How would you approach this task?

• How would you design an ML model to predict hotel occupancy rates? You work for an online booking website like Booking.com and need to build an ML model to predict hotel occupancy rates for any given date. What data would you use to train your model, and how would you evaluate its performance?

• What is the expected number of good ads rated by different types of raters?
• Suppose we have 100 raters each rating one ad independently. What's the expected number of good ads?
• Now suppose we have 1 rater rating 100 ads. What's the expected number of good ads?

• Suppose we have 1 ad, rated as bad. What's the probability the rater was lazy?

• 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).

• How do you calculate the sample variance of a list of integers? Write a function that takes a list of integers and outputs the sample variance, rounded to 2 decimal places.

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

• What's the probability of rolling at least one 3 with 2 dice?

• What's the probability of rolling at least one 3 given (N) dice?

• What is the probability of finding an item on Amazon's website given its availability in warehouses? Given the probabilities that an item is available at warehouse A (0.6) and warehouse B (0.8), calculate the probability that the item would be found on Amazon's website.

• 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.

• 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 representing the date and time for each transaction, write a query to get the last transaction for each day. The output should include the id of the transaction, datetime of the transaction, and the transaction amount, ordered by datetime.

• 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.

• 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.

• Develop a function calculate_rmse to calculate 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 that represents the predictions y_pred and another with the target values y_true.

What is the average salary for a Data Scientist at Booking.Com?

Q: What is the interview process like for a Data Scientist at Booking.com? The interview process at Booking.com typically includes multiple stages. You start with an HR phone interview followed by a technical online test. Then, you have a technical phone interview with data scientists discussing a past project and solving a business case. Successful candidates are invited to an onsite interview in Amsterdam involving multiple rounds including technical interviews, business cases, and a final interview with a senior team member.

Q: What type of technical questions can I expect in the interviews? Technical questions often focus on A/B testing, machine learning models (e.g., linear regression, LDA model), and business case solutions related to Booking.com’s operations. You may also be asked to explain past projects in detail, covering the algorithms used, the reasoning behind your choices, and the impact of your work.

Q: How do I prepare for the business case interviews? To prepare for the business case interviews, it’s essential to practice thinking through problems from a business and data science perspective. Be ready to outline how you’d solve various Booking.com related scenarios, such as segmenting customers for recommendations or measuring the impact of a change in the cancellation policy. Utilize resources from Interview Query to practice and gain insights into solving these types of cases.

Q: What qualities are Booking.com looking for in a Data Scientist? Booking.com values strong analytical and technical skills, a good understanding of machine learning models, and the ability to translate business problems into data science solutions. They also look for candidates who can articulate their thought process clearly and connect technical metrics to business outcomes. Skills in experimental design and causal inference are also highly valued.

Q: What is the company culture like at Booking.com? The interview process reflects a collaborative and open culture at Booking.com. Candidates often note the friendly and professional demeanor of the interviewers. Despite occasional negative experiences reported, many find the structured interview process transparent with detailed feedback. Booking.com seeks to foster an environment where data scientists can thrive and contribute to both technical and business goals.

Embark on your journey to join Booking.com as a Data Scientist, where you’ll encounter a well-structured and comprehensive interview process designed to measure both your technical prowess and business acumen. Through multiple stages including HR screenings, technical phone interviews, business case evaluations, and onsite interactions, you'll have the opportunity to present your past projects, solve intricate business problems, and demonstrate your understanding of machine learning and statistical methods.

While the process can be lengthy and challenging—requiring detailed project discussions, business cases, and real-time problem-solving—it offers great insights into what it takes to excel at Booking.com. Be prepared to address topics such as A/B testing, segmentation strategies, and recommendation systems. Keep in mind that the interviewees are friendly, often providing valuable feedback and aiming to see you succeed. However, experiences can vary, with some candidates facing inconsistent information and unprofessional attitudes.

For more insights about the company, check out our main Booking.com 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 Booking.com's interview process for different positions.

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 conquer every Booking.com data scientist interview challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!