Interview Query

Top Data Analyst Behavioral Interview Questions

Data analyst behavioral questions tend to be vague and open to interpretation. Learn how to approach these questions, so you don't get tripped up.

Data Analyst Behavioral Interviews: What to Expect

When analysts prepare for interviews, they tend to go heavy on technical skills. They’ll write SQL practice queries, study up on common definitions, and run through some data analytics case studies.

But one area they don’t spend nearly enough time on is the behavioral interview.

Data analyst behavioral questions are tricky to answer. Without some solid preparation, you’re likely to respond with long-winded answers that confuse the interviewer and leave you counting down the minutes until it’s over.

In general, behavioral interviews for data analyst roles ask open-ended questions that assess your experience, your ability to communicate, and if you’re the right fit for the company and role. You might expect questions in these four areas:

  • Past job experience
  • Culture/company fit
  • Technical communication
  • Data sense

Fortunately, preparing for behavioral questions is a straightforward process. We’ve highlighted some tips and common questions that data analysts can use to study for behavioral interviews.

Looking for more data analyst interview questions? See our guide: Top Data Analyst Interview Questions.

How to Prepare for Analyst Behavioral Interviews

The key to answering this type of question is specificity. Use specific examples, clearly outline steps you took to solve problems, and describe any lessons or new skills you learned in the past. One helpful tip: Consider using a framework to structure your answers.


The STAR method is a commonly used framework for behavioral questions. With this method, you would first describe the Situation, cover the Task you had to solve, describe the Action you took, and finally, highlight specific Results you achieved.

This is particularly helpful for outlining past projects and handling experiential questions. For example:

Q1. Tell me about a time when you used data to solve a problem.

You might respond with:

  • Situation - In a previous hospitality job, we noticed our conversion rate was decreasing.
  • Task - My goal was to better understand our customers to help the sales and marketing team develop more effective UX strategies and promotions to improve conversion rates.
  • Action - In the past, many of the marketing decisions had been made based on our average customer. But I felt that there was an overreliance on the average, and decided to cluster customers and better segment them.
  • Result - We found that our real customers weren’t very similar to the average metrics that were being used. The customers segments I created helped to better guide product and UX decisions, resulting in a 30% lift in conversion rate.

This is a general outline. You’ll want to add more depth, but it gives you an idea of how to use the STAR framework to structure your answers.

Job Experience Questions for Data Analysts

For interviewers, behavioral questions are a useful tool for cross-checking a resume, and seeing if someone’s career level aligns with the role. Therefore, a lot of behavioral questions for data analysts will explore prior experiences, past projects, and how you’ve handled adversity in the past.

Q1. Describe a data project you worked on. What were some of the challenges you faced?

When you’re asked about a project, use a format like the STAR method. You should walk the interviewer through the project, from start to finish. Begin with the business problem and conception. Describe your approach and how you executed it. And always end with the results.

Hint: Project questions give you a chance to show off your iterative process and how well you work with stakeholders.

Q2. Describe an analytics experiment that you designed. How were you able to measure success?

Data analysts get tasked with experimenting with data to test new features or campaigns. Many behavioral questions will ask about experiments, but also tap into how you approach measuring your results.

With questions like these, be sure to describe the objective of the experiment, even if it was a simple A/B test. Don’t be afraid to get technical; explain the metrics you used and the process you used to quantify the results.

Q3. Describe a time when you were going to miss a deadline. How did you respond?

Q4. Tell me about a project in which you had to clean and organize a large dataset.

Technical Communication Behavioral Questions for Data Analysts

Many behavioral questions will assess your ability to communicate tools and techniques, your results and insights to a lay audience.

Q1. How would you convey insights and the methods you use to a non-technical audience?

You’ll find a lot of variations to this question, but the objective is always the same: to assess your ability to communicate complex subject matter and make it accessible. Data analysts often work cross-functionally, and this is a key skill they must possess.

Have a few examples ready and use a framework to describe them. You might say:

“The marketing team wanted to better segment customers, so, after gaining an understanding of their motivations and goals for the project, I presented several segmenting options and talked them through trade-offs.

I felt that K-means clustering would be the best method for their objective, so I made a presentation about how the method worked, potential strategies for visualizing the new segments, described key benefits, and ultimately, talked about potential trade offs.”

Q2. How comfortable are you presenting your insights?

Interviewers want to know you’re confident in your communication skills and can effectively communicate complex ideas. With a question like this, walk the interviewer through your process:

  • How you prepare
  • Strategies you use to make data accessible
  • What tools you use in presentations

Also, the ability to present virtually is vitally important in today’s market. Have several recent experiences to talk about, both in-person and virtual. This is a common question in data visualization interviews.

Q3. Have you ever had to use data to persuade stakeholders?

Q4. What are some effective ways to make data more accessible to non-technical people?

Q5. Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?

Data Sense Questions in Analyst Interviews

Interviewers want to understand your ability to assess data quickly, know when something’s amiss, or have ideas about where to start when investigating a problem.

Q1. Describe a time when you spotted an inconsistency. How did you respond?

Successful data analysts help businesses identify anomalies and respond quickly. For data sense questions, think about a time that you were able to spot an inconsistency in the data, and the steps you took to address it. A question like this lets you show your data-savviness and aplomb for statistics or analytics.

Q2. Talk about a time you were surprised by the results of an analytics project.

Q3. Describe a time when you made a mistake and used the wrong dataset. How were you able to identify your error?

Q4. Talk about a time when your assumptions were wrong. How did you respond?

Q5. Tell me about a time when you had to use data to make a decision.

Culture Fit Behavioral Questions

These questions are designed to see if you’re the right match for the team. They assess your passion for analytics, how you work with others, and why you want to work for the company.

Q1. Why did you choose analytics as a career? Or what made you want to be a data analyst?

This question gets asked a lot, especially for entry-level data analyst positions, and yet, it trips up a lot of candidates. It’s not enough to simply state, “I have always loved statistics.” Be honest about what makes you passionate about data and analytics.

Maybe it was a project you did in an undergraduate class or a book you read that ignited your curiosity. Maybe you read an interesting case study and wanted to help businesses better utilize data. The key is to show genuine passion for data and analysis in your response.

Q2. Why are you interested in working for our company?

Again, this is a super common question that trips up a lot of candidates. Have a strong answer for this question. You might focus on the company’s data culture, highlighting some of the interesting ways they’ve used data.

Or let’s say you know a data analyst already with the company who you’ve talked to about the culture. You might mention the connection, and that you’ve heard good things and want to play a part.

Q3. What are some qualities that every data analyst should have?

Q4. Do you think it’s important for data analysts to be creative? Why or why not?

Q5. Do you prefer a particular niche in analytics, like say, customer analytics? Why or why not?

Q6. Do you work well under pressure? Do you work well on teams?

Conclusion: Practicing for a Data Analyst Behavioral Interview

Practice is the best way to get better at data analyst behavioral interview questions. The more questions you practice, the more confident you’ll become in talking about past experiences.

Plus, it’ll give you practice using frameworks to structure your answers. The STAR method is useful, as is the SCORE framework for behavioral interviews. Although you don’t have to use a framework, they will give you a way to effectively communicate your ideas, in a logical well-organized manner.

—> Continue your data analyst interview prep with our guide: Top Data Analyst Interview Questions.