EXL Data Analyst Interview Questions + Guide in 2024

EXL (NASDAQ: EXLS) is a global analytics and digital solutions company that excels at turning data into actionable insights, thereby improving client business outcomes. Renowned for its expertise in insurance, healthcare, banking, and retail industries, EXL leverages advanced analytics, AI, and cloud solutions to transform complex operations. Headquartered in New York and boasting over 54,000 professionals across 50 offices worldwide, EXL is committed to innovation, collaboration, and excellence.

Stepping into the role of Data Analyst at EXL requires robust SQL, Python, and data visualization skills. Candidates are assessed on their proficiency in coding, statistics, and machine learning and ability to handle complex datasets, derive insights, and present data-driven recommendations to stakeholders.

Ready to take the plunge? This guide will prepare you for navigating the interview processes, providing insights into the commonly asked EXL data analyst interview questions you might encounter and offering tips to help you succeed. Let’s dive in!

The interview process usually depends on the role and seniority; however, you can expect the following on an EXL data analyst interview:

Recruiter/Hiring Manager Call Screening

If your CV is shortlisted, a recruiter from EXL’s Talent Acquisition Team will make contact to verify key details such as your experience, qualifications, and technical skills. Behavioral questions might also be a part of this screening process.

In some cases, the hiring manager may also join the call to discuss the role and the company and answer any questions you might have. This round usually lasts about 30 minutes.

Aptitude Test

The first technical step involves an aptitude test focusing on various skills such as SQL, Python, Statistics, and Machine Learning. Be prepared, especially with SQL, as it is crucial for working as a Data Analyst at EXL. The test may include questions about joins in SQL, unions, and union maximums.

Technical Interviews

EXL’s interview process for a Data Analyst position consists of two technical rounds.

First Technical Round

This round involves discussing your resume, projects, and internships in detail. You might be asked to introduce yourself, explain your project work, and solve puzzles or guesstimates. Questions may include SQL queries, probability, econometrics, Gauss-Markov assumptions, and Bayes’ theorem.

Second Technical Round

This interview will delve into advanced SQL, programming, and mathematics-related questions. Expect case studies, econometrics questions, a deep dive into SQL queries, data modeling, and machine learning techniques such as regression and classification methods. Proficiency in Python and understanding of data visualization tools might also be tested.

Managerial Interview

Once you clear the technical rounds, you will proceed to a managerial interview. This interview will focus on your overall fit for the team, understanding of the business, past project experiences, and how you align with team goals. It may include a more detailed discussion about job responsibilities and performance expectations.

HR Interview

The final stage involves an HR interview, during which compensation, work culture, and company policies will be discussed. It’s also your chance to ask final questions about the role and EXL.

Typically, interviews at EXL Service vary by role and team, but common data analyst interviews follow a fairly standardized process across these question topics.

1. What are the drawbacks of having student test scores organized in the given layouts?

Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in “messy” datasets.

2. 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. Devise a strategy to locate the mouse using the fewest number of scans.

3. How would you select Dashers for Doordash deliveries in NYC and Charlotte?

Doordash is launching delivery services in NYC and Charlotte and needs a process for selecting dashers. Determine the criteria for selecting dashers and whether the criteria should be the same for both cities.

4. What factors could bias Jetco’s study on-boarding times?

According to a study, Jetco, a new airline, has the fastest average boarding times. Identify factors that could have biased this result and what you would investigate further.

5. How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company?

A B2B SAAS company wants to test different subscription pricing levels. Design a two-week A/B test to evaluate a pricing increase and determine if it is a good business decision.

6. Write a SQL query to select the 2nd highest salary in the engineering department.

Write an SQL query to select the second-highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

7. Write a function to find the maximum number in a list of integers.

Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

8. Create a function convert_to_bst to convert a sorted list into a balanced binary tree.

Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should be balanced, meaning the height difference between the left and right subtree of all the nodes should be at most one.

9. Write 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 can_shift to determine if one string can be shifted to become another.

Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

11. How much should we budget for the coupon initiative in total?

A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider. The app services (N) riders. Calculate the total budget needed for the coupon initiative.

12. What is the probability of both riders getting the coupon?

A driver using the app picks up two passengers. Determine the probability that both riders will receive the coupon.

13. What is the probability that only one of them will get the coupon?

A driver using the app picks up two passengers. Determine the probability that only one of the riders will receive the coupon.

14. What is a confidence interval for a statistic, and why is it useful?

Explain what a confidence interval is, why it is useful to know the confidence interval for a statistic, and how to calculate it.

15. What is the probability that item X would be found on Amazon’s website?

Amazon has a warehouse system where items are located at different distribution centers. In one city, the probability that item X is available at warehouse A is 0.6 and at warehouse B is 0.8. Calculate the probability that item X would be found on Amazon’s website.

16. Is this a fair coin?

You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair.

17. What are time series models, and why do we need them?

Describe what time series models are and explain why they are needed when we have less complicated regression models.

18. How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician?

Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician, tailoring your explanations to their understanding levels.

19. What happens when you run logistic regression on perfectly linearly separable data?

Given a dataset of perfectly linearly separable data, describe the outcome when logistic regression is applied.

20. How would you evaluate and validate a decision tree model for predicting loan repayment?

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

21. How would you justify using a neural network model to non-technical stakeholders?

If tasked with building a neural network model to solve a business problem, explain how you would justify the model’s complexity and explain its predictions to non-technical stakeholders.

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

Describe the process by which random forest generates its forest and explain why it might be preferred over logistic regression for certain problems.

Here are some quick tips on how you can ace your EXL data analyst interview:

1. Strengthen Your Basics: Be strong in SQL, Python, Statistics, and Machine Learning basics. EXL places a significant emphasis on SQL skills.

2. Thoroughly Review Your Projects: Be prepared to discuss your past projects and internships in detail. You should be able to explain your role, methodologies, and outcomes clearly.

3. Understand Business Context: EXL values data-driven decision-making. Make sure you can connect your data analysis skills to real-world business scenarios, especially in banking, credit card data, or other relevant domains you’ve worked in.

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

What is the work environment like at EXL?

EXL offers a supportive and collaborative work environment. The company values innovation, excellence, and integrity and aims to deliver successful outcomes for its employees and clients. Interviewees noted a formal yet compassionate interview process, with HR particularly supportive.

What is expected from me in terms of project work and collaboration?

As a Data Analyst, you will be expected to analyze complex datasets, develop dashboards, and present actionable insights. Collaboration with cross-functional teams to understand data requirements and deliver solutions is key. You will also be involved in data cleaning, validation, and ensuring data quality and accuracy in your reports and models.

EXL champions a culture of outcomes and data-driven success. By following the shared tips and showcasing your analytical talents, you stand to excel not only in the interviews but also in driving EXL’s commitment to optimizing data for business growth.

For more details, explore EXL’s website and our EXL Service Interview Guide to leverage additional resources for your preparation. Good luck with your interview at EXL, where your data expertise can truly make an impact!