Revolut Data Analyst Interview Questions + Guide in 2024

Revolut is among the most popular cross-border payment apps with a full banking license granted by the European Central Bank. It operates in 37 countries and has over 35 million customers.

As a data analyst at Revolut, your responsibilities may include developing fraud detection algorithms, analyzing customer spending patterns, optimizing user experience, and enhancing financial services through collaboration with cross-functional teams.

The interview process for the Revolut data analyst role mainly revolves around database queries, a few statistics, and some behavioral questions.

Expect a multi-level interview process at Revolut for the data analyst role. It may include multiple rounds of telephone, video, and on-site interviews, depending on the position you’re applying for.

While the interview process varies with the requirements, here’s what typically happens in an interview for a data analyst position at Revolut:

Filling Out the Online Application Form

If you’ve not been encouraged by a Revolut recruiter to apply for the data analyst role, you’ll need to go through their Career Portal to apply.

The online application form is usually a questionnaire. You’ll be asked to submit your contact details, resume, employer branding, salary expectations, and technicalities regarding visa permission and notice period.

During the application process, you may also need to answer a few job-specific questions about your skills and experience.

Initial Phone Interview

If successful, you’ll be invited for a 15-20 minute phone or video interview focusing on behavior. The Revolut recruiter and hiring manager will evaluate your soft skills and verify your job experiences as a data analyst.

However, most hiring managers conduct video interviews where they also present coding challenges (SQL and Python).

Online Assessments

The next stage of the Revolut data analyst interview is an online assessment. You’ll receive an email evaluating your success in the previous stage and inviting you to complete a set of Revolut tests. The nature and complexity of the questions will depend on the particular data analyst role and the seniority of the position you’re applying for.

To approach the online assessment confidently, prepare for numerical reasoning, database queries, and situational judgment problems.

On-Site Interview

As a successful candidate, you’ll be invited to the nearest Revolut office to meet the technical managers, team leaders, and potential colleagues personally. The managers will interview you one-on-one and may also conduct a group exercise with other candidates. The interviewers will assess your answers and let you know their decision via email or phone.

Partner Interview

In this final stage of the Revolut data analyst interview process, you’ll meet the hiring manager, division leader, and department director. While this round doesn’t include technical assessments, they may continue to evaluate your soft skills and desire to join Revolut.

Behavioral questions, SQL fundamentals, and query optimizations are primarily considered in Revolut data analyst interviews. While rare, fundamental statistical questions are also asked during these interviews. As a data analyst candidate, be prepared to demonstrate your analytical skills.

In this section, we’ve discussed a few common data analyst questions with example answers. Use them to upskill your technical proficiency and refine your approach to behavioral questions.

1. What would your current manager say about you? What constructive criticism might he give?

Your Revolut interviewer wants to assess your ability to reflect on feedback and your openness to accepting constructive criticism.

How to Answer

Acknowledge your strengths and areas for improvement based on potential feedback from your manager. Focus on how you plan to or have addressed any constructive assessments of your work.

Example

“My current manager would likely commend me for my strong analytical skills and attention to detail in handling financial data. However, he might suggest improving my communication skills in presenting complex findings to non-technical stakeholders. I have actively addressed this by taking communication workshops and seeking feedback from colleagues on my presentations.”

2. What makes you a good fit for Revolut?

Your understanding of Revolut’s business model, culture, and values and how your skills align with the company’s needs will be checked with this question.

How to Answer

Highlight specific skills, experiences, or attributes that make you uniquely suited to contribute to Revolut’s goals. Connect your strengths to the company’s values or objectives.

Example

“I believe my background in financial analysis and data-driven decision-making aligns well with Revolut’s innovative approach to disrupting the traditional banking sector. Additionally, my experience in fintech startups has equipped me with the adaptability and agility necessary to thrive in Revolut’s fast-paced environment. I’m also passionate about the company’s mission to democratize financial services, and I’m eager to contribute to that vision.”

3. Tell me about a time when your colleagues disagreed with your approach. What did you do to bring them into the conversation and address their concerns?

This question assesses your conflict resolution, teamwork skills, and ability to handle disagreements professionally.

How to Answer

Describe a specific situation where colleagues disagreed with you. Explain your approach to resolving the conflict and highlight the outcome of your efforts.

Example

“In a previous project, my colleagues and I disagreed on the best approach to analyzing a dataset for a client presentation. Some team members preferred a traditional statistical analysis, while I advocated for a machine learning approach. To address their concerns and encourage collaboration, I organized a meeting to discuss our approaches. I actively listened to their perspectives, acknowledged their valid points, and demonstrated how incorporating elements of both approaches could enhance the analysis. Ultimately, we agreed on a hybrid approach that satisfied everyone and improved the quality of our final presentation.”

4. What is your approach to resolving conflict with co-workers or external stakeholders, partially when you don’t really like them?

With this question, your conflict resolution skills, professionalism, and ability to work effectively with diverse personalities as a data analyst are assessed thoroughly.

How to Answer

Describe a conflict resolution approach that maintains professionalism and prioritizes finding a solution over personal feelings.

Example

“When faced with conflict, particularly with individuals I may not have a strong rapport with, I work to maintain a professional demeanor and resolve the issue. I approach the situation with empathy, actively listen to the other party’s concerns, and strive to find common ground for a solution suitable to everyone. Focusing on resolving the conflict rather than personal feelings ensures that our work relationships remain productive and respectful.”

5. How do you prioritize your tasks and stay organized when you have multiple deadlines?

The interviewer will assess your time management, prioritization, and organizational skills, which are especially important in a fast-paced environment like Revolut.

How to Answer

Describe your approach to prioritizing tasks based on deadlines, importance, and impact on organizational goals. Highlight specific strategies or tools you use to stay organized and manage multiple deadlines effectively.

Example

“When faced with multiple deadlines, I first evaluate the urgency and importance of each task based on its impact on organizational goals. I then prioritize tasks accordingly, focusing on high-impact deliverables that are due soon. To stay organized, I utilize project management tools like Trello or Asana to create detailed task lists, set deadlines, and track progress. Additionally, I regularly communicate with team members to ensure our priorities are aligned and adjust my schedule as needed to finish projects on time without sacrificing quality.”

6. Given a table of flights, extract the 2nd flight with the longest duration between each pair of cities. Order the flights by the flight id ascending.

Note: For any cities X and Y, (source_location=X, destination_location=Y) and (source_location=Y, destination_location=X) are counted as the same pair of cities.

Note: If there are fewer than two flights between two cities, there is no 2nd longest flight.

Example:

Input:

flights table

Column	Type
id	INTEGER
destination_location	VARCHAR
source_location	VARCHAR
plane_id	INTEGER
flight_start	DATETIME
flight_end	DATETIME

Output:

Column	Type
id	INTEGER
destination_location	VARCHAR
source_location	VARCHAR
flight_start	DATETIME
flight_end	DATETIME

As a data analyst, your ability to write SQL queries to extract specific data from a database table and order it according to certain criteria is assessed with this question.

How to Answer

You can use an SQL query to join the flights table with itself on the pair of cities and filter the second longest flight duration for each pair of cities.

Example

SELECT [f1.id](http://f1.id/), f1.destination_location, f1.source_location, f1.flight_start, f1.flight_end
FROM flights f1
JOIN flights f2 ON f1.destination_location = f2.destination_location
AND f1.source_location = f2.source_location
AND [f1.id](http://f1.id/) <> [f2.id](http://f2.id/)
GROUP BY [f1.id](http://f1.id/), f1.destination_location, f1.source_location, f1.flight_start, f1.flight_end
HAVING COUNT(DISTINCT f2.flight_end) = 1
ORDER BY [f1.id](http://f1.id/) ASC;

7. Given a table called user_experiences, write a query to determine the percentage of users who held the title “Data Analyst” immediately before holding the title “Data Scientist.”

Immediate is defined as the user holding no other titles between the data analyst and data scientist roles.

Example:

Input:

user_experiences table

Column	Type
id	INTEGER
position_name	VARCHAR
start_date	DATETIME
end_date	DATETIME
user_id	INTEGER

Output:

Column	Type
percentage	FLOAT

Your Revolut interviewer will evaluate your SQL skills in writing queries involving complex conditions and aggregations.

How to Answer

Write an SQL query to calculate the percentage of users who transitioned directly from the position of data analyst to data scientist.

Example

SELECT
COUNT(*) * 100.0 / (SELECT COUNT(*) FROM user_experiences) AS percentage
FROM user_experiences ue1
JOIN user_experiences ue2 ON ue1.user_id = ue2.user_id
WHERE ue1.position_name = 'Data Analyst'
AND ue2.position_name = 'Data Scientist'
AND ue2.start_date = (SELECT MIN(start_date)
FROM user_experiences
WHERE user_id = ue2.user_id
AND start_date > ue1.end_date);

8. You are a chef preparing for an important event. You downloaded three recipes and imported each as a separate table: recipe1, recipe2, and recipe3 into your database. Each recipe requires grocery items in various quantities. Write a query that sums up the total mass of each grocery item required across all recipes.

Input:

recipe1 table:

Column	Type
grocery	VARCHAR
mass	INTEGER

recipe2 table:

Column	Type
grocery	VARCHAR
mass	INTEGER

recipe3 table:

Column	Type
grocery	VARCHAR
mass	INTEGER

Output:

Column	Type
grocery	VARCHAR
total_mass	INTEGER

This question assesses your ability to write SQL queries to aggregate data from multiple tables, a critical skill required to work as a data analyst at Revolut.

How to Answer

Use an SQL query to join the three recipe tables and calculate the total mass of each grocery item required across all recipes.

Example

SELECT grocery, SUM(mass) AS total_mass
FROM (
SELECT grocery, mass FROM recipe1
UNION ALL
SELECT grocery, mass FROM recipe2
UNION ALL
SELECT grocery, mass FROM recipe3
) AS combined_recipes
GROUP BY grocery;

9. Given a users table, write a query to return only its duplicate rows.

Example:

Input:

users table

Column	Type
id	INTEGER
name	VARCHAR
created_at	DATETIME

This question evaluates your SQL proficiency in identifying and filtering duplicate records from a database table.

How to Answer

Write an SQL query to select only the duplicate rows from the users table.

Example

SELECT id, name, created_at
FROM users
WHERE id NOT IN (
SELECT MIN(id)
FROM users
GROUP BY name, created_at
);

10. What are the logistic and softmax functions? What is the difference between the two? What makes them useful in logistic regression?

This question assesses your understanding of logistic and softmax functions, their differences, and their relevance to logistic regression.

How to Answer

Provide a brief explanation of logistic and softmax functions, highlighting their differences and why they are useful in logistic regression.

Example

“Logistic function maps any real-valued number to the range [0, 1], making it suitable for binary classification tasks in logistic regression.

Softmax function is a generalization of the logistic function to multiple classes. It takes a vector of real-valued scores as input and outputs a probability distribution over multiple classes. It ensures that the sum of the probabilities of all classes is equal to 1, making it useful for multiclass classification tasks in logistic regression.”

11. Can you explain the difference between INNER JOIN, LEFT JOIN, and RIGHT JOIN?

This question checks your understanding of different types of SQL joins and when to use each one in data analysis.

How to Answer

Discuss what each SQL join does and the purpose it may solve while running a query.

Example

“In an INNER JOIN, only the rows with matching values in both tables are returned. In a LEFT JOIN, all rows from the left table are returned along with matched rows from the right table. In a RIGHT JOIN, all rows from the right table are returned along with matched rows from the left table.”

12. How do you handle NULL values in SQL queries?

This question enables the Revolut interviewer to evaluate your understanding of databases and your ability to deal with NULL values effectively in SQL queries.

How to Answer

Provide examples of functions such as COALESCE and ISNULL with operators such as IS NULL or IS NOT NULL to answer the question effectively.

Example

“In SQL queries, I manage NULL values by employing the IS NULL or IS NOT NULL operators to filter out rows with NULL values. For instance, when I want to retrieve rows where a certain column doesn’t have NULL values, I use the IS NOT NULL operator in my WHERE clause.

Additionally, I use functions like COALESCE to handle NULL values by replacing them with a default value. This ensures that my queries return meaningful results, even when dealing with NULLs. For example, I might use COALESCE in my SELECT statement to display a default value in case the column contains NULLs.”

13. Explain the difference between GROUP BY and ORDER BY in SQL.

This question examines your understanding of SQL query syntax related to data manipulation and organization, critical skills a data analyst needs.

How to Answer

Explain what the syntaxes do and when they’re used in data manipulation and organization.

Example

“GROUP BY is used to group rows with the same values into summary rows. It’s handy when we want to perform aggregate functions like COUNT(), SUM(), AVG(), etc., on these groups. On the other hand, ORDER BY is all about sorting the result set. When we use ORDER BY, we tell the database how to arrange the rows based on specified criteria, whether in ascending or descending order. It doesn’t affect grouping or perform any calculations; it just changes the display order of rows in the result set.”

14. How would you read a CSV file into a Pandas DataFrame in Python?

The Revolut interviewer will evaluate your proficiency in handling data manipulation tasks using Python libraries like Pandas.

How to Answer

Mention you’ll use the read_csv() function from the Pandas library to read the CSV file into a dataframe. Specify any necessary parameters, such as file path, delimiter, and encoding, if required.

Example

“To read a CSV file into a Pandas DataFrame in Python, I would use the read_csv() function from the Pandas library. For example:”

import pandas as pd
df = pd.read_csv('file.csv')

15. Explain the purpose of the “if name == ‘main’:” statement in Python scripts.

Your understanding of Python script execution and module structure will be assessed through this question.

How to Answer

Discuss how the statement checks whether the script is being run directly or imported as a module. Mention how it only allows code within the block to run if the script is the main program.

Example

“The purpose of the ‘if name == 'main' :” statement in Python scripts is to check if the script is being run directly. Code within this block will only execute if the script is the main program. This is useful for separating reusable code into modules and preventing it from executing when the module is imported.”

16. Explain the concept of standard deviation and how it is calculated.

This question assesses your understanding of statistical concepts and ability to calculate standard deviation.

How to Answer

Start by explaining the concept of standard deviation as a measure of the dispersion or spread of a dataset around its mean. Then, discuss the formula for calculating standard deviation, which involves taking the square root of the variance. You can mention that it provides a measure of how much the values in a dataset differ from the mean value.

Example

“Standard deviation is a statistical measure used to quantify the amount of variation or dispersion in a dataset. It indicates how much individual data points differ from the mean of the dataset. The formula for standard deviation involves taking the square root of the variance, which is the average of the squared differences from the mean. It’s calculated by finding the square root of the sum of squared deviations from the mean, divided by the number of observations. In Python, you can use libraries like NumPy to compute standard deviation efficiently, for example, using the np.std() function.”

17. Discuss the importance of indexing in SQL databases. What types of indexes are commonly used, and how do they impact query performance?

This question will evaluate your understanding of database indexing and its impact on query performance as a data analyst.

How to Answer

Explain the concept of indexing in SQL databases, a data structure technique that improves the speed of data retrieval operations on a database table. Discuss the importance of indexing in improving query performance by reducing the time required to retrieve data. Mention commonly used types of indexes, such as B-tree and hash indexes, and explain how they impact query performance differently.

Example

“Indexing in SQL databases is crucial for optimizing query performance by enabling faster data retrieval operations. Indexes are data structures that store a sorted reference to key values in a table, allowing the database engine to locate rows quickly. Commonly used types of indexes include B-tree indexes, which are well-suited for range queries and sorting, and hash indexes, which are efficient for equality comparisons. By creating appropriate indexes on columns frequently used in queries, we can significantly improve the speed of data retrieval.”

18. Describe a scenario where you would use a subquery in SQL. What are the advantages and disadvantages of using subqueries?

Your Revolut interviewer will assess your understanding of subqueries in SQL and their application in different scenarios.

How to Answer

Define a subquery as a query nested within another query. Provide a scenario where a subquery would be useful, such as retrieving data based on a condition derived from another query’s result. Discuss the advantages of using subqueries. Then, mention disadvantages.

Example

“A scenario where a subquery would be beneficial is when we need to retrieve data from one table based on a condition derived from the result of another query. For example, finding all customers who have made purchases above a certain threshold. Subqueries simplify such queries by breaking them into smaller, more manageable parts. However, using subqueries can sometimes lead to performance issues, especially if they are not optimized properly. They may also make the query harder to understand for others maintaining the code.”

19. How would you handle imbalanced datasets in a classification problem using Python? Discuss different techniques and their implications.

This question assesses your knowledge of techniques for handling imbalanced datasets in machine learning classification problems, which are required skills for a data analyst.

How to Answer

Explain what imbalanced datasets are, where one class is significantly more prevalent than the others. Discuss techniques for handling imbalanced datasets using different evaluation metrics and using algorithms specifically designed for imbalanced datasets. Explain the implications of each technique on model performance and interpretability.

Example

“In Python, we handle imbalanced datasets in classification problems using various techniques. One approach is resampling, where we either oversample the minority class or undersample the majority class to balance the dataset. Another technique is to use different evaluation metrics such as precision, recall, and F1-score instead of accuracy, which may be misleading in imbalanced datasets. Additionally, algorithms like Random Forest with class weights or ensemble methods like AdaBoost can be effective for handling class imbalance. However, it’s important to consider the implications of each technique on model performance and interpretability, as oversampling can lead to overfitting and undersampling can discard valuable data.”

20. Discuss the concept of statistical power in hypothesis testing. How does it relate to sample size and effect size?

Your understanding of statistical power in hypothesis testing and its relationship with sample size and effect size will be assessed with this question.

How to Answer

Define statistical power as the probability of correctly rejecting a null hypothesis when it is false. Explain that increasing the sample size generally increases statistical power, while larger effect sizes and higher significance levels also contribute to higher power.

Example

“Statistical power in hypothesis testing is the probability of correctly rejecting a null hypothesis when it is false, indicating the ability of a test to detect if an effect exists. It’s influenced by several factors, including sample size, effect size, and significance level. Increasing the sample size generally increases statistical power because it reduces the variability of the estimate and makes it easier to detect effects. Additionally, larger effect sizes and higher significance levels also contribute to higher statistical power. Therefore, when designing experiments or studies, it’s essential to consider these factors to ensure adequate statistical power for detecting meaningful effects.”

It’s not enough to have the basic programming ability to crack the Revolut data analyst interview.

Your ability to communicate, answer behavioral questions, and dive deep into the working principles behind the solutions will also contribute to your success as a candidate.

Let’s talk about what you should get ready for to ace your data analyst interview at Revolut.

Understand Revolut and Its Requirements

Research Revolut’s mission, values, and services to tailor your answer to their preferences and requirements. Know why they need a data analyst and emphasize your relevant skills during the interview.

Refine Your Technical Skills

Despite being a heavily analytical field, develop your skills as a data analyst to understand technical problems and offer effective solutions.

Refine your programming proficiency in Python, SQL, and R for data analysis and visualization. Practice SQL questions to further familiarize yourself with database queries.

Also, remember to go through our Data Analytics Learning Path to better understand the concepts and answer the data analyst interview questions.

Have Fundamental Statistical Knowledge

Although statistical questions are rare during a data analyst interview at Revolut, understanding fundamental statistics is critical.

Our Statistics & AB Testing Course can help you learn the basics and prepare for potentially difficult questions.

Prepare Behavioral Questions

Always be prepared with case studies and past experiences to answer the common data analyst behavioral questions.

Practice them thoroughly to avoid getting lost in the question’s phrasing and purpose. Be mindful of demonstrating what you did to solve the particular problem and what positive outcome you could extract from it.

Attend Mock Interviews

Whether you’re an experienced data analyst or seeking your first opportunity, you can always find loopholes in your prepared answers.

Join our peer-to-peer mock interviews to enhance your communication skills and refine your approach to behavioral and technical questions. Working through these interviews will help minimize hesitation and reduce anxiety, enabling you to interview confidently.

Explore our detailed guide to gain more details about preparing for data analyst interviews.

Where can I see Interview Query’s salary information for Revolut’s data analyst role?

You can check our salary guide page for information on data analyst salaries. However, we don’t have specific details about salaries for data analysts at Revolut right now because we need more data. If you know anyone who works or has worked as a data analyst at Revolut, we’d really appreciate any info they can share.

For a general overview of the industry standards, you may go through our data analyst salary guide.

Where can I find people who have had experience working at Revolut as a data analyst?

You can find information about other people’s experiences in the Revolut data analyst role on our Slack community. Additionally, you may find blog posts or forums where individuals share their experiences working at Revolut.

Does Interview Query have job postings for the Revolut data analyst role?

Yes, we do have job postings for the Revolut data analyst role on our dedicated Job Board. However, the openings for each position are subject to availability.

We’ve discussed key questions and the interview process for your upcoming Revolut data analyst interview. It all comes down to having the answers to statistics, programming, and behavioral problems.

Ensure that you have covered all the basics and can effortlessly answer our data analyst interview questions. Also, don’t forget to explore our main Revolut interview guide if you have further queries. Moreover, see if you can effortlessly answer data analyst Excel and Python questions.

Moreover, check out our discussion on the data scientist and software engineering positions at Revolut and explore other top companies where you can work as a data analyst.