Two women and a man sitting at a table, working on a laptop.
Take me through how you’d estimate the number of tourists visiting Dubai each February.

This type of story-based problem can help you see how your interviewee approaches a basic data task without the help of computers or working with a data set. You’re not looking for a specific answer here, but a solid approach. They should be able to clearly explain how they would identify the variables and what steps they would take to uncover the answer.


What statistical analysis tools and database software have you previously used? What are your favorites and why?

The requirements of your open position will determine what sort of responses are most relevant to you. But every data analyst should know ​the current dominant data language, ​SQL, ​particularly for online businesses like marketplace and e-commerce. Listen for references to other relevant ​database concepts and business intelligence (BI) tools as well​, such as SPSS or SAS—and a willingness to learn new software and tools if needed.

How would you go about measuring the business performance of our company, and what information do you think would be most important to consider?

While every interviewee will hopefully research your company thoroughly before speaking with you, a top data analyst also knows how to ask good questions to understand the business’s needs. Ideally, they will start a dialogue with you here, giving you an idea of how familiar they are with your industry’s practices and norms. ​This question can also provide a window into the sort of projects they’d be eager and able to tackle for your company if hired.

Do you have experience developing algorithms and databases from scratch?

If your team doesn’t already include a data engineer, you will probably need your data analyst to move comfortably between these roles—so find out if the interviewee’s experience matches the expectations of the job. Listen for responses that indicate they’re accustomed to moving and extracting data from large data warehouses, and know how to write their own ETL scripts. If the answer is yes to all, then they should be able to handle the data mining necessary to accomplish the desired analysis.

What are some best practices for data cleaning? What are the steps you take?

Data cleaning is an essential process that enhances the quality of data. The candidate should be able to list some best practices, like sorting the data by different attributes or breaking a large dataset down to increase iteration speed. They should also be able to explain why they favor particular practices over others, based on their own experience.

Tell me about a time when you think you demonstrated good data sense.

A data analyst with good “data sense” can look at a chart or table and sense that something is off—say, a conversion rate that’s too low, or a bookings number that seems wrong. Untangling data issues like this can come from experience, but also from a deep understanding and talent for statistics, business, and economics. If a candidate can confidently share a story about a time they sniffed out an inconsistency and worked through the appropriate channels to solve it, then they’re likely a data-savvy problem-solver—and a great addition to your team.

What’s been the greatest cost-reducing strategy you were able to implement as a result of your analysis and reporting?

A good data analyst is adept at spotting trends and opportunities for savings and growth. Beyond their ability to mine, use, and analyze data, look for candidates that demonstrate solutions-oriented traits—such as persistence or creativity—that can turn a pesky task like cost reduction into a company triumph.

Describe your most complex data project from start to finish—what were the most difficult challenges, and how did you handle them?

Having the candidate talk you through a large-scale assignment will give you a good insight into their overall experience level as a data analyst. Responses will vary, but acceptable answers should indicate that the candidate has a strong iterative process for tackling challenging projects—from mapping out the data and creating an algorithm to mining the data, checking for accuracy, and modifying as needed. It should also be clear that feedback from the stakeholders plays a critical role in their process. If the candidate has taken a project from conception to actionable results—and has worked through complex data challenges to get there—then this is an experienced data analyst worth moving to the next round.

Tell me about a time when you designed an experiment. How did you measure success?

Data analysts will often help conduct experiments to determine how successful a campaign or feature will be. They should be able to explain the objective of the experiment (like a simple A/B test to decide which of two campaigns to roll out on a wider scale), what metrics they used to track and quantify the results, and why.

How do you explain your findings and processes to an audience who might not know what a data analyst does?

Communication is a huge part of an effective data analyst’s job. This is a role that often requires working directly with management, engineers, and end users to gather assignments and requirements, provide detailed status updates for large data projects, and build communication bridges across departments. So you’ll want to see that your candidate can express their ideas well to help others understand, that they’re accustomed to ​formatting data in an easy-to-read manner, and ​that they’re passionate about explaining the importance of data to others.

What do you think are the three best qualities that great data analysts share?

Great data analysts have a mix of both hard and soft skills. Candidates may value different skills for different reasons, but a strong answer may mention traits like ​problem-solving and analytical thinking, coupled with the ability to​ get along well with others. Whatever their answer, a great candidate will demonstrate an understanding that a well-rounded analyst is more than just a number cruncher.

What drew you to data analysis as a career?

With the help of qualified analysts, Big Data can offer companies huge insights—and this may be one of the most exciting developments of our information age. A data analyst who’s passionate about ideas like this, and who shows a genuine interest in statistics, economics, logic, and reasoning is likely a good fit for the role and will make a great addition to your culture.