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Data Analyst Interview Questions

Close-up shot of a data analyst. Graphs, numbers, and charts can be seen in the reflection of their glasses.Text reads:
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Data analysts collect and interpret data to identify trends and patterns. Data analyst duties and responsibilities typically include extracting information from large data sets, performing statistical analysis to make predictions and identifying and recommending new ways to improve a business based on data.

When hiring a data analyst, look for ​​strong problem-solving skills, knowledge of data analysis tools and languages (e.g., SQL, Excel) and a good understanding of the data analysis process. Great candidates for your data analyst role may also have big picture thinking skills, an investigative mindset and proficiency with one or more scripting languages (Python, R, etc.).

Ask 5-10 of the following interview questions to get a better sense of a candidate’s data analysis skills and experience.

  1. What do data analysts do? See answer
  2. Which data analysis software are you well-versed in? See answer
  3. What was your most difficult data analyst project? See answer
  4. Why did you go into data analysis? See answer
  5. Your employer wants you to find all sales quota data from the past three months to see if recent incentives enhanced employee productivity. How does data cleaning factor into your analysis? See answer
  6. Can you talk about a time where you couldn’t meet a deadline as a data analyst?
  7. Can you explain how you would estimate how many shoes could potentially be sold in New York each June? How do you reach a conclusion?
  8. What is your process when you start a new data analysis project?
  9. What is data modeling and how do you use it in your analysis?
  10. How would you define the Hierarchical Clustering Algorithm? When would you use it?
  11. Can you tell me how to use logistical regression when analyzing data sets?
  12. What is the difference between big data and data? Do you have experience working with big data?
  13. How many statistical methods are you familiar with? Can you provide me with a few examples?
  14. Are you comfortable using data analysis software? Which programs have you used in previous roles?
  15. How do you differentiate between data profiling and data mining? Can you give me an example of when you would use data profiling or data mining?
  16. How do you conduct an analysis when there are missing data figures? What does your process look like?
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8 Data Analyst Interview Questions and Answers

Q:

What do data analysts do?

A:

This question is basic but serves an essential function. It weeds out the candidates who lack a rudimentary understanding of data analysis. It also lets you compare how well various candidates understand data analysis. What to look for in an answer:

  • Coverage of each step
  • Mention of soft skills, such as communication
  • Discussion of how data analysts benefit a company
Example:

“In general, data analysts collect, run and crunch data for insight that helps their company make good decisions. They look for correlations and must communicate their results well. Part of the job is also using the data to spot opportunities for preventative measures. That requires critical thinking and creativity.”

Q:

Please talk about a time when you could not meet a deadline.

A:

This question gets into how well candidates handle stressful situations. You’re looking for a data analyst who can anticipate when a deadline is not going to work and who can find a solution. Past behavior is a good predictor of future behavior. What to look for in an answer:

  • Ability to see big picture
  • Decisiveness and being proactive
  • Answers that do not blame others
Example:

“At HTWW Company, my team was having a hard time finding data from certain sources to do an environmental impact study. I contacted the client and explained why we were struggling and what we were doing to remedy the problem. It was still relatively early in the process, so I was able to get a one-week extension.”

Q:

Which data analysis software are you well-versed in?

A:

This question lets you assess if candidates have the hard skills you need and can tell you what areas they might need training in. It is also another way to ensure basic competency. What to look for in an answer:

  • Software the job ad emphasized
  • Experience with the software
  • Ability to speak with familiarity
Example:

“I have a breadth of software experience. For example, at my current employer, I do a lot of ELKI data management and data mining algorithms. I can also create databases in Access and make tables in Excel.”

Q:

What was your most difficult data analyst project?

A:

With a question like this, you glean insight into how candidates approach and solve problems. It also gives you a better idea of the type of work they have done. What to look for in an answer:

  • Explanation of how challenge(s) were overcome
  • Lack of blaming others
  • Discussion of why the project was difficult
Example:

“My most difficult project was on endangered animals. I had to predict how many of [animal] would survive to 2020, 2050 and 2100. Before this, I’d dealt with data that was already there, with events that had already happened. So, I researched the various habitats, the animal’s predators and other factors, and did my predictions. I have high confidence in the results.”

Q:

Take a few minutes to explain how you would estimate how many shoes could potentially be sold in New York City each June.

A:

Many interviewers pose questions that let them see an analyst’s thought process without the aid of computers and data sets. After all, technology is only as good and reliable as the people behind it. What to look for in an answer:

  • Ability to identify variables/data segments
  • Ability to communicate thought process
  • Creativity
Example:

“First, I would gather data on how many people live in New York City, how many tourists visit in June and the average length of stay. I’d break down the numbers by age, gender and income, and find the numbers on how many shoes they may already have. I’d also figure out why they might need new shoes and what would motivate them to buy.”

Q:

What is your process when you start a new project?

A:

This question lets you measure candidates’ organizational skills and how well they anticipate. It also gives you an opportunity to see if candidates’ leadership or work styles are compatible with your company culture. What to look for in an answer:

  • Clear steps
  • Deliberate process
  • Consideration of deadline
Example:

“My first step is to take some time to look over the project so that I can define the objective or problem. If I’m having a hard time figuring that part out, I reach out to the client. Next, I feel out the data to see what’s there, how reliable it is and where it comes from. I think about what could be the best way to model it and whether the project deadline seems to work.”

Q:

Why did you go into data analysis?

A:

This query is a good way to get to know candidates as people. It can serve as an icebreaker at the beginning of an interview or, if it comes at the end, as a gentle way to bring your question portion to a close. What to look for in an answer:

  • Focused replies
  • Personality
  • Specifics
Example:

“When I was 10, I wanted to do a paper route to get money for a class trip. My dad said no. I took it upon myself to give him a report on how much I would earn, how long it would take and why the trade-offs such as not being able to sleep in were worth it. That process led me to fall in love with data analysis.”

Q:

Your employer wants you to find all sales quota data from the past three months to see if recent incentives enhanced employee productivity. How does data cleaning factor into your analysis?

A:

Data analysts help companies answer questions about daily operations by retrieving information from databases and other types of data infrastructure. Based on their findings, they compile reports and make inferences about what that information confirms or denies about business operations. This question allows interviewers to gauge a candidate's ability to isolate clean data to use in their analysis. It also allows them the determine a candidate's level of experience with data cleaning in their daily job. The candidate's answer should emphasize:

  • Data cleaning competency
  • Detail-orientation
  • Investigative mindset
Here's an example of a good response to this question:
Example:

"When pulling sales quota data from the past three months, it is important to remember that not all data is entered the same. For example, some employees might enter their sales quotas as percentages while others enter them as monetary figures. This means that I need to identify these inconsistencies as I retrieve data, and I either need to change all sales quota averages to percentages or monetary figures. Without consistency, I can't complete accurate statistical calculations to contribute to my analysis."

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