So you’re looking for an entry-level data analyst job. Congratulations on choosing one of the most popular vocations in the technology realm! Data analytics was rated as one of Career Karma’s top 25 tech jobs in 2021—along with such lauded status comes high demand and high salaries, but that also means there will be stiff competition for entry-level data analyst positions.
Data analysts who land the best jobs will be well-prepared for interview questions that don’t just query technical skills but also delve into preferred work styles, collaborative abilities, and approaches to problem-solving.
In this guide, you’ll learn how to prepare for common entry-level data analyst interview questions. Here’s the topics we’ll cover in this guide:
- What does an entry-level data analyst do?
- What skills and education do you need to become a data analyst?
- How to prepare for an entry-level data analyst interview
- Sample entry-level data analyst interview questions and answers
- Key takeaways and what you should do next
You can use the clickable menu to skip ahead to any section. Now, let’s begin!
What does an entry-level data analyst do?
As an entry-level data analyst, you will collect, clean, and interpret datasets to answer a question or solve a problem. Data analysts work in all sectors and industries—a data analyst who works in new product development for a large corporation might parse big data on customer preferences to determine what features of a certain product consumers find most valuable. A data analyst working for a health research organization might analyze data on a particular disease to see how it affects a certain population segment.
There are different types of data analysis. Descriptive analysis finds out what happened, diagnostic analysis looks at why it happened, predictive analytics forms projections for the future, and prescriptive analysis focuses on what actions to take.
The duties of the entry-level data analyst are, broadly, the following:
1. Identifying and collecting the data to be analyzed
Analysts often collect data themselves for their data analytics projects. Data may come from surveys, tracking visitor activity on a company website, or buying datasets from data collection organizations.
2. Cleaning the data in preparation for analysis
Big data, or raw data, is unstructured and might contain duplicates, errors, or outliers. Cleaning the data entails maintaining the quality and uniformity of data in a spreadsheet or through a programming language so that the interpretations are accurate and not skewed.
You can learn more about data cleaning and its importance to the data analytics process in this article.
3. Analyzing the data
During the data analytics process, data analysts use specific tools and programming languages to make their work more accurate and efficient. Some of the most common data analytics tools used in the field include:
4. Interpreting the results of the analysis
The goal of interpreting data is to find patterns or trends that will answer questions or provide insights. Communicating the results to management and stakeholders through visualizations, such as graphs, charts, reports, and presentations, are a key part of a data analyst’s job.
What skills and education do you need to become a data analyst?
When it comes to entering the field as an entry-level data analyst, you’ll find that technical skills are what are most important to an employer. Most data analysts will also have bachelor’s degrees in fields like mathematics, statistics, or computer science, and the best-paid analysts will have master’s and doctorate degrees. However, entry-level data analysts that have a strong technical background will generally stand a better chance of being hired than those who don’t.
Technical skills for entry-level data analysts
Professional certificates can teach you the basics in hard, technical skills like SQL or statistics. Certification in certain areas increases your value to an employer. If you’re looking at a data analytics certification, make sure that the curriculum includes modules on some, if not all, of the following technical skills:
- Database Management. Examples of impressive credentials when it comes to technical skills are having a good working knowledge of database tools like Microsoft Excel and SQL. SQL handles large datasets and is widely regarded as a necessity for data analysis.
- Programming. Languages, such as Python or R, are also used for large datasets to perform complex equations. Check to see which languages are relevant to the industry and role you are targeting.
- Data Visualization. Tools like Tableau, Jupyter Notebook, and Excel are tools used to create visuals to present the findings of data analysis and recommendations.
- Statistics and Math. Knowledge of statistics and math will guide you when choosing the best tools to solve a particular problem or perform a specific job. Math skills can help you catch errors and better understand the results from analysis.
Data analysis is a popular field, but there are courses that will teach you the hard skills you need as a data analyst in less than a year.
Soft skills for data analysts
Technical skills are a critical component of a data analyst’s toolbox. However, companies also want to see that a data analyst has problem-solving skills, the ability to communicate and work with a team, and some familiarization with the industry they are targeting. These skills are not manifested through credentials or certification, so the interview is typically an opportunity for the company to delve into a candidate’s soft skills, as well as their technical skills.
How to prepare for the interview
It’s important to remember that each job interview situation is different. While some questions asked by recruiters or interviewers will be quite predictable, there will be others that will surprise you. Thoroughly research the company before your interview to understand what type of data analytics the company does and what exactly your job will entail.
The job description and website will provide some information, but a good idea is to reach out to a data expert within the company, who can give you an inside look into what your job might be like. To find a contact, check the company’s LinkedIn page, or call your HR contact and see if they can recommend someone you could chat to before your interview. If you can envisage your future role, you will be much better prepared for any question that comes up.
Next, we’ll look at some sample questions by category, with examples of how to answer them.
Sample entry-level data analyst interview questions and answers
The entry-level data analyst interview questions you will be asked will generally fall into three broad categories:
- Questions about you—your work style, how you approach problems, and how you collaborate with others.
- Questions about your technical skills and knowledge.
- Behavioral interview questions. You will be asked to explain how you’ve coped with an event in the past, because that is considered a good predictor of how you will behave in a similar context in the future.
When preparing your answers to the questions in each category, try to embody three characteristics: the ability to listen and interpret information, the ability to solve problems, and a drive to learn.
Sample questions about you
These questions are designed to see if you are a good fit for the company. For example, If the job requires you to work independently—but you prefer to collaborate with a team—you will not be a good fit for the job. Here are some typical questions that determine your suitability.
Why do you want to be a data analyst?
Although this question seems broad, your answer should be specific to the job at hand. A good answer is to describe some aspect of the company’s operations and explain why you want to be a part of that. This demonstrates a high level of interest in that company. Check out the company’s website and, particularly, press releases to find out the company’s latest news and activities.
Sample answer: I’ve been following the company’s developments in machine learning algorithms applied to embedded finance security solutions. Embedded banking and finance is an emerging trend, and I would love the opportunity to collaborate on these projects and to learn more about how data analytics helps companies build their strategies.
Tell me about yourself.
This question is almost guaranteed to be asked in an interview, yet few people are prepared to answer it. Consider this a chance to not only introduce yourself, but to sell yourself for the role. Tell the interviewer about relevant work or study that you have been involved in that shows you are a good fit.
Sample answer: I have been a data technician for the past two years, and have had the opportunity to work on customer analytics for marketing. I understand that this job is oriented toward parsing customer data with an eye to new product development. It’s a field I’d like to gain more expertise in.
Why should we hire you?
It can be difficult to sell yourself, but take a deep breath and go for it. Tell the employer about your accomplishments that make you the best person for the job, and use a measurable result to illustrate them. Align what you say with the requirements of the job posting or what you have learned through your research.
Sample answer: I am certified in SQL and Python and, for the last year, I have been applying those skills to product analysis and development at my current job. One product has already been chosen to go to market, and we are one month ahead of the project deadline. I am confident that I can help to reduce your concept-to-market timelines.
Why are you leaving your current employer?
If you were fired or let go, this question is particularly difficult, but it needn’t be. Be honest, because the hiring company is likely to contact your last employer. Whatever the circumstances of your leaving, your answer can be short, and you can move to another topic that is positive.
Sample answer: My last employer suffered during the recent economic downturn and had to downsize. As a result, I was laid off. Since then, I’ve been focusing on learning Python. I’ve used it for some freelance work, which has really given me more confidence and motivation.
If you are leaving for other reasons, be careful not to denigrate your last employer and keep it positive.
Sample answer: I sense that there is not much room for professional growth or exposure to new areas with my current employer. This job really appeals to me because the company is involved in many different data research projects that are unique and cutting-edge.
Questions about your technical skills and knowledge
Which data analyst software are you trained in?
The interviewer is not just assessing the depth of your data analytics repertoire here, but is also assessing your learning patterns. When answering this question, show the interviewer your capacity to learn quickly and apply that learning.
Sample answer: I recently earned a SQL certification online in my spare time. Once certified, I led a project team in an analysis that led to unexpected insights and changed the company’s new product strategy.
Here are some other technical entry-level data analyst interview questions you may be asked that you should know the answers to.
- What programming languages have you learned, and to what proficiency?
- What’s the largest data set you’ve worked with?
- What is data cleaning, and what are the best ways to practice this?
- Name the best tools used for data analysis.
- How would you go about measuring the performance of our company?
- What are the common problems faced by data analysts during the data analysis process?
- What is the difference between data profiling and data mining?
- Name some data validation methods used by data analysts.
- What is an outlier?
- Explain normal distribution.
What are the advantages of version control?
Sample behavioral interview questions
When answering behavioral questions, you will be asked to explain a past experience and how you coped with it. By answering these questions, you have an opportunity to show your emotional intelligence and your soft skills, such as communication, collaboration, and leadership. Here are some examples.
Walk me through your portfolio. Can you explain your most successful/most challenging data analysis project?
You’ve hit the jackpot with this question! It’s an opportunity to showcase why you are perfect for the job. Describe a situation where you excelled. For example, perhaps you were asked to be team leader by your peers. One method to use to structure your response to behavioral questions is to use the STAR method.
STAR stands for Situation (the context), Task (the problem), Action (what you did to solve the problem, and Result (the outcome). Your answer should include all of those components.
Sample answer: For the last two projects, I was nominated as team leader (Situation). The last project was complex, and the team wasn’t quite sure how to approach it. We had to take a legacy solution and break it down to determine what components were of most value to the user (Task). I asked the team to suggest ways to attack it (Action). I led brainstorming sessions and we changed our approach a couple of times to better understand the data. We are currently re-developing the product based on our analysis (Result).
Can you tell us about a situation that revealed a weakness?
For this question, turn a weakness into a strength. Choose something innocuous, like the tendency to stick with what you know, rather than trying a new approach. You could explain that you have learned to be more open-minded when it comes to new approaches to data analytics.
Sample answer: I have a tendency to use the tools that I know. But I’ve learned to listen to others and to try new approaches. You can always reiterate if you don’t get the desired results.
Can you tell us about a time when you faced a deadline that you couldn’t meet? What did you do?
This question is a behavioral question that is examining how you anticipate the time required to do a task and your approach to a problem. It is also asking how you communicate to others that you have a problem and perhaps negotiate for additional time or resources.
Sample answer: I once was given a data analytics project that needed to be done by a strict deadline (Situation). The data was complex and the cleaning process took a lot longer than expected. Also, the client was expecting to see certain categories of data, which would have required extensive manipulation (Task). I met with the client to tell them that more time was needed, but they were not willing to compromise on the deadline. (Action). Ultimately, I was able to get them to agree to provide additional resources and another analyst so that we could deliver the results on time (Result).
Questions about your approach and work style preferences
Tell us an example of a conflict you had with someone and how you resolved it?
Conflict resolution is a daily task in the workplace, even for an analyst. But conflict leads to progress. What is key here is to show your ability to listen and try new ideas.
Sample answer: One project I worked on was categorizing data so that the clients obtain accurate and meaningful information. (Situation). Some of the solutions we used were legacy tools that were not quite what we needed, but some of the analysts wanted to keep using them. We had to choose new tools (Task). The team brainstormed possible approaches that we had not yet really considered (Action). We found a way to integrate the key functions that some of the analysts really wanted to retain. (Result).
How do you communicate insights and visualizations to a stakeholder that hasn’t worked with them before?
This question is asking whether you can communicate complex information in a convincing and digestible way. Use the same STAR technique.
Sample answer: My last presentation to my management group was an analysis of a payments solution and how it affected conversions (Situation). I visually demonstrated the process from start to finish and how the customer responded to the new payment system (Task). I explained the data and what the results showed in terms of whether the solution was improving sales (Action). Based on the findings, the company decided to expand its embedded banking offerings (Result).
Tell me about a time when you got unexpected results.
Data analysts should let the data tell the story and know how to overcome selection bias. Use this question to show your openness and interest in learning new things from data.
Sample answer: We often get unexpected results! That’s why I love data analytics. The last project that I worked on produced some interesting trends. We validated the data and the findings, and ultimately suggested adding a new product that aligned with what we were seeing in the customer data.
Key takeaways and what to do next
There is no way to know exactly what entry-level data analyst interview questions will come up in your interview. However, thorough research will help you to understand the company, its culture, the type of person they are looking for, and what skills are of most value. That way, you can plan what scenarios you will use in your answers.
The bottom line is that data analytics is a lucrative field—and a growing one. Data analytics is a growing field, with attractive starting salaries for entry-level data analysts. If you’re reading this article in anticipation of transitioning to a career as a data analyst, we recommend the following articles: