Data analyst job interview: ace these common questions

Interested in becoming a data analyst but nervous for your job interview? You’ve come to the right place. We’re breaking down what a data analyst is and the most common questions you’ll be asked in an interview. Plus, the best way to answer them - directly from the pros.

For even more guidance looking for a data analyst job, apply for our Data Science Bootcamp for lifetime career services support and guidance to help start and grow your career. You’ll gain access to our experienced team of mentors and guides who work closely with you to ensure you’re ready to launch your data career. In fact, 87% of our grads find a job within 180 days because of our personalized, and hands-on approach to education and career training.

What is a Data Analyst?

Before we dive in, what exactly is a data analyst? A data analyst examines sets of data so they can gather insights about various situations and create meaning from disordered information. They look for patterns, relationships, and other insights so they can help companies solve problems, propel their business forward, and stand out from the competition.

A large part of the job is critical thinking and working with numbers and you’ll frequently be asking questions, collecting data, cleaning data, analyzing results, and interpreting the results.

Not sure if data is for you? Take our interactive skills gap quiz to find out the skills best suited for you.

Top 3 Skills Required for a Data Analyst

While working as a data analyst, you’ll frequently use three skills - analytical, technical, and communication. According to Marie Gallagher, data analyst at La Presse, one of Quebec’s largest newspapers, and instructor at Lighthouse Labs, you’ll need to be able to effectively communicate with others both to understand the context of their situation and what they need, as well as to present information to them. To expand on this further, here are three skills you absolutely need to master as a data analyst:

1. Data cleaning and preparation

One of the most important skills as a data analyst, preparing data involves finding data from different sources and combining it in one place so it’s ready for analysis. Data cleaning involves handling “missing and inconsistent data that may affect your analysis.”

2. Writing, listening, and communication skills

Having strong communication skills will make your job way easier as you have to collaborate with others frequently and it’s important they understand your analysis. It’s also important to listen and understand stakeholders to ensure you’re including the right information in your reports.

3. Creating data visualizations

This is a key responsibility in every data analyst job as it helps everyone understand the trends and patterns you’re discovering. By creating plots and charts to display the data and findings visually you’re not only helping others understand what you’re discovering but you’re allowing yourself to see it in a different way, potentially allowing you to find additional information that may have gotten lost in the numbers.

How Do I Prepare for a Data Analyst Interview?

Woman interviewing for a data analyst job Preparing to interview for a data analyst position calls for some forethought. First, research the company that you are interviewing with and the team this position is within. Second, determine your relevant skills and experience, which you want to bring up during the interview. Have examples of past projects and achievements to cite in conversation. Next, practice typical interview questions and get comfortable with the answers you want to deliver in the interview. Then, go into the interview with a positive mindset; whether you get a job offer or not, approach this experience as a learning and growth opportunity.

Finally, it helps to do some research on the company itself for any previous candidate interview experience. Sites like Glassdoor provide crowd-sourced data points on the types of questions companies ask, the culture, and what the interview process is like.

Data Analyst Interview Questions and Answers

Applying for a data analyst job is both exciting and nerve-wracking. Before attending your data analyst interview, it’s important to prepare yourself. Make sure you have a solid understanding of what a data analyst does, including common tasks they complete, software they use, and how to solve certain problems. Don’t forget to think back on your past experiences so you can recall moments that you can use as examples while answering questions. Read on to prepare yourself for your next interview, and land that dream job of yours:

Why do you want to become a data analyst?

This question helps the interviewers understand your thought process behind choosing the role. When answering, make sure to explain the key reasons you want to be a data analyst and what key skills you have for the job.

Potential Answer:

"As a data analyst, it’s my job to help you make more informed decisions to help the company improve. I’m good with collecting data, communicating my findings to others, and I find market research interesting."

What are the key components of a data analyst job?

This question tests your knowledge on what the required skills are for a data analyst. Have a few points in the back of your mind so you’re not listing the first skills that come to mind.

Potential Answer:

"Have a solid understanding of various programming languages such as Javascript and XML, databases like SQL and Db2, and have extensive knowledge on reporting packages.

  • Understand Big Data and be able to analyze, organize, collect, and disseminate it efficiently.
  • Develop substantial technical knowledge in fields such as database design, data mining, and segmentation techniques.
  • Understand how to analyze massive datasets. A few examples are SAS, Excel, SPSS."

What is “data cleansing”? What’s the best way to practice?

Computer screen with data showing analysis One of the most common questions in a data analyst job interview - so make sure to have an answer! Simply explain what data cleaning is and how to do it.

Potential Answer:

"Data cleansing involves detecting errors and inconsistencies and removing them from the data to improve its quality. Common ways to clean data are:

  • Compartmentalizing data according to their attributes
  • Breaking large chunks of data into smaller datasets to clean them
  • Analyzing the statistics of each data column
  • Creating a set of scripts that solve common cleaning tasks
  • Keeping the information organized to facilitate easy addition or removal from the datasets, if required.”

Have you previously used quantitative and qualitative data within the same project? Tell us about it.

Using both quantitative and qualitative data within a project is important to gain a full understanding of the project. When answering this question, talk about the project that required the most creative thinking.

Potential Answer:

“I’ve had a few projects where I had access to qualitative survey data, but I realized that I can enhance the validity of my recommendations by implementing data from external survey sources as well. When I combined the two types of data together in a product development project, it yielded great results.”

Which data analyst software are you comfortable using?

This question tells your employer that you have the hard skills needed to solve their problems and have the basic knowledge needed to perform your job. When answering, make sure to include the software the job ad mentioned, experience with the software you have, and use familiar terminology.

Potential Answer:

“I’ve used a range of software as a data analyst so far. For example, I currently do a lot of ELKI data management and data mining algorithms. I’m also very comfortable creating databases in Access and making tables in Excel.”

Tell us about your most difficult project as a data analyst? How did you solve it?

If an interviewer asks you this question, they want to understand how you approach and solve problems. It also helps them understand what type of projects you’ve done in the past. When answering, besure to explain the project, how you solved it, and what the result was. Don’t blame others or explain why the project was difficult.

Potential Answer:

“My most difficult project was finding out the percentage of pollution in the United States. I had to figure out which states are the most polluted and I also compared the pollution levels in the last 10 years and predicted what it would be in the upcoming 10 years. I had some data, but I did further research on the most polluted states to help finalize my future predictions. After my analysis, I’m confident in the results.”

How do you handle pressure and stress?

Data visualization job interview example including questions and answers The point of this question is to understand how well you work in stressful situations. Try and think of a time when you were given a difficult task or multiple tasks and excelled in the project, rather than a time that you created a situation that was stressful for yourself.

Potential Answer:

“I find I work really well under pressure as I enjoy working in a challenging environment and thrive under quick deadlines. I often perform my best work when I have the pressure of a deadline coming up. For example, I once had 5 large projects due within the same two weeks. Although it was stressful, I created a detailed schedule that broke down the projects into smaller assignments and staggered the due dates. I ended up completing the projects on time with no added stress.”

What should you do if data is missing or suspected?

This is another question that the interviewer asks to gain an understanding of how you solve problems. When answering, list a few ways you would personally approach the problem.

Potential Answer:

"If data is missing or suspected, I would try:

  • Using the deletion method, single imputation method, and other model-based methods to detect missing data.
  • Preparing a report containing all the information about the missing or suspected data
  • Replacing the invalid data with a proper validation code, and;
  • Analyzing the suspicious data to assess its validity"

What’s your experience in giving presentations to various audiences?

Communication is a very important skill as a data analyst, and that includes being able to give strong presentations. Employers are looking for candidates who have great analytical skills and the confidence to present their findings in an eloquent and easy-to-understand way to upper-level management and non-technical co-workers. When answering this question, make sure to mention the following:

  • Size of the audience you presented to
  • Who was in the audience (ex. executives)
  • The general knowledge the audience had
  • If the presentation was in person or remote.

Potential Answer:

"I’ve presented to various audiences. Some were smaller with many upper-level management and executives present, while others were larger and included coworkers and clients that had different knowledge backgrounds. The largest presentation was around 50 people. All of these presentations were done in person, except for a one-on-one zoom call with the CEO.”

Have you worked in an industry similar to ours?

By answering this question, you’re demonstrating that you have industry-specific skills and experience. If you haven’t worked in that particular industry before, just be honest and make sure you explain how you can apply your current skills to benefit the company.

Potential Answer:

“I’ve previously worked in the healthcare industry but I think there are quite a few overlaps with the financial industry. One being data security. Both these industries have large amounts of highly sensitive information that has to be kept secure and confidential. Because of this, data is often restricted so it takes more time to complete an analysis. Having dealt with this many times, I’ve learned how to be efficient when it comes to passing through the security and how to clearly state the reasons behind requiring certain data."

What’s your favourite software to use?

This is a straightforward answer that helps the employer understand what you enjoy working on. Just be honest and explain what program you like best and why. If you enjoy a software that the company currently uses, it would be helpful to state that one. If you find the role requires specific software skills that you don't have, do a few tutorials ahead of hand and demomstrate that you're a quick learner and willing to pick up on these tools quickly.

Potential Answer:

“I personally love Microsoft Excel because they’re available at almost every company and I’m very comfortable using them. Since they’re so accessible, there is a lot of training on them, so I can continually improve my skills to achieve great results. I also love working with visualization software like Tableau and Power BI, as well as other tools like Jupyter Notebook, Seaborn, Apache Spark, Docker, Flask, and more to help round out my skill set.”

What step of data analysis do you enjoy the most? Why?

Although you may not love all the steps of data analysis, use this question to show your strengths instead of talking about what you don’t like.

Potential Answer:

“If I had to choose one favourite step, it would be analyzing the data. I enjoy finding evidence to support or refute various hypotheses and I think it’s really interesting to find unexpected learnings from the data. You can learn so much from data and it always helps with my analysis of future projects.”

What scripting languages have you used? Which one do you like best?

Although it’s helpful to know more than one language, as many companies use a variety, it’s more important to demonstrate your enthusiasm for learning new scripting languages and pointing out your fluency in the ones you have a solid understanding of. When answering this question, keep in mind what languages that company uses. If you’ve used it, state why you like it. If you haven’t, explain which language is your favourite but also mention how you’re open to learning others.

Potential Answer:

“My favourite scripting language is SQL, because I've worked with it the most so far, so I’m quite confident using it. But, I’ve also been learning Python and R. I’ve found my knowledge in SQL helps me better understand Python, so I’m able to learn it faster.”

How have you used statistics in your work?

Understanding basic statistics knowledge is important for data analysts. This question helps the interviewer see how much you know about statistics.

Potential Answer:

“I have used statistics before - mostly calculating the mean and standard variances, as well as significance testing. I’ve also determined the relationship between two variables in a data set while working with correlation coefficients.”

Why should we hire you?

A common question in any interview that you should always be prepared for. Think about what truly makes you the best fit for this question. Keep your answer short and confident, explaining exactly what you have to offer.

Potential Answer:

“I have previous experience working with projects that had similar problems to yours. I also have excellent communication skills and further technical knowledge that would be an asset to your company. The mix of technical and team skills I bring to the table make me an ideal fit for this role.”

What do you think are the most important skills a data analyst needs to work efficiently with people that have different roles, knowledge, and duties?

As a data analyst, you’ll be reporting your findings to various people often - and most of the time they don’t have a background in technical knowledge. This means you have to be excellent in interpreting your findings using non-technical language. By answering this question, you’re showing that you’re capable of working with various people who don’t speak your “language”.

Potential Answer:

“I believe patience, understanding, and showing that you care are all very important when working with people of different educational backgrounds. I often work with stakeholders and the most common challenge is trying to answer a question I don’t have the answer to yet, due to the limited data I have at the moment. When this situation arises, I use my available data to answer the question as closely as possible and then propose how I can find the information that we don’t currently have. This not only shows that I’m dedicated to the project but that I also respect their needs.”

What soft skill(s) are you best at? Why?

Non-technicals skills are important in any job to ensure that you’re working efficiently with others and can perform your job at a high level. You should be aware of your strengths that help you in your job, outside of the typical data analyst skills. State 2-3 skills and briefly (and confidently) explain why you think you’re good at them.

Potential Answer:

“I believe my leadership skills help me take action easier and help other members on my team. It also helps me continuously want to learn and grow so I can be the best leader possible - whether that means developing further soft skills or technical skills. My ability to listen is also very helpful as I’m generally interested in my field and learning from others and I want to ensure that I understand the project so I can complete it to the best of my ability.”

Do you have any questions?

Every interview you go to will end with this question, but it’s important to have some questions prepared instead of just saying no. Try asking any of the following questions to show that you’re interested in the position and eager to work there:

  • Can you explain a typical day for a data analyst at your company?
  • What’s the work environment like in the office?
  • What’s the company culture like?
  • Are there any options to further my learning so I continually grow in my role?

While answering any questions yourself, make sure you sound natural and let your personality shine. You don’t want to sound like you memorized a speech. Try and have a conversation with your interviewer and be confident in what you can bring to the table. Remember to always tie back your experience or examples to the company and position you're interviewing with and for. Not only does it show understanding of the scope of the role, it shows that you did your research ahead of time which can go a long way.

What are the key requirements for becoming a data analyst?

To become a data analyst, you should have a combination of the following skills:

  • Structured Query Language (SQL)
  • Microsoft Excel
  • Critical Thinking
  • R or Python-Statistical Programming
  • Data Visualization
  • Presentation Skills
  • Mathematics and Statistics

Generally, the following responsibilities fall within the data analyst role so you should be comfortable with:

  • Utilize data science skills to become experts in the performance of specific businesses and departments.
  • Tend to be specific to a single team or department, like Sales, Marketing, or Customer Experience.
  • Implement basic scripts and pipeline code, but typically are not expected to develop software.

Start Your Data Analytics Career with Lighthouse Labs

If you don’t have the answers to most of these answers but want to be a data analyst, we’d recommend joining our 12-week Online Data Science Bootcamp.

We understand that everyone learns at different paces and you may have further questions outside of your time with our instructors. To help you, you’ll have access to a mentor that you can contact any time on Slack so all your questions can be answered in real time. This program is for anyone who wants to become a data scientist or data analyst.

Have questions about the bootcamp or Lighthouse Labs in general? Talk to one of our alumni to get an insider’s perspective.