Data AnalystInterview Questions
Data analysts translate data into information, information into insight, and insight into practical solutions. This data may be used in countless ways from determining how to reduce costs for transportation, to producing new materials, to solving staffing issues that cost the company money.
Data analysts can specialize in many fields, including operations, finance, and marketing. They possess the skills necessary to provide business leaders with insight which can be used in other aspects of Information Technology (IT) as well.
Data analyst responsibilities may include:
- Acquiring data from primary and secondary data sources
- Cleansing data to ensure it is in the proper format
- Interpreting data to look for trends
- Conducting life-cycle analysis
- Developing new process improvements based on discoveries
- Filtering data to correct code problems
Data analysts are essential for providing management with valuable insights into company data. In order to best utilize that information, a skilled data analyst will:
- Possess an eye for detail in order to identify code problems
- Be able to translate technical data into layman’s terms
- Possess superior interpersonal skills to maintain pleasant working relationships
- Have strong organization and prioritization skills to manage large sets of data
- Utilize creative thinking to provide revolutionary business insight
In order to secure an entry-level position, candidates will need to possess a bachelor’s degree in mathematics, computer science, or a related field. Certification is available for analysts wishing to specialize in a certain area.
If you’re getting ready to interview for a position as a data analyst, you can prepare by researching the company as much as possible. Learn about the 9 things you should research before an interview.
Salaries for data analysts range between $91K and $146K with the median being $117K.
Factors impacting the salary you'll receive as a data analyst include:
- Degrees (bachelor's, master's, PhD, or equivalent)
- Years of experience
- Reporting structure (seniority of the manager to whom you report, number of direct reports)
- Level of performance - exceeding expectations
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Data Analyst Interview Questions
Question: In your own words, can you tell me what a data analyst does?
Explanation: This is a general question asked early in the interview and designed to establish rapport and start understanding your qualifications. It not only gives you the opportunity to make a strong first impression, but you can also direct the interview in a direction you’re comfortable with by the way you answer this question. You may want to talk briefly about how you became a data analyst and then discuss your approach to this work.
Example: “I became interested in using data to discover trends and learn new things while still in high school. My natural curiosity and systematic approach to problem solving drew me to this field. In college, I learned about the techniques and tools as well as the methodologies used to analyze large and complex sets of data in order to discover specific information that was helpful in improving business processes. I believe data analysis is about distilling information people can use to make decisions or initiate actions from large sets of data collected from the environment within which they are working. This work fascinates me because it is always changing and presenting new challenges.”
Question: What do you know about our business, and what value will you bring as a data analyst?
Explanation: By asking this question, the interviewer is attempting to determine if you’ve taken the time to learn about their business and can explain your value proposition. They are already aware of the contributions a data analyst can make, but they want to see if your perception of your value aligns with their expectations. Another reason they ask this type of question is because some candidates will not take the time to learn about the company’s business before interviewing. This will automatically disqualify the candidate from further consideration.
Example: “I’ve done quite a bit of research into your company and the products you produce. I’m very impressed by your recent growth and expansion into new markets. I believe the value I can bring to your organization is to help you quickly identify future growth opportunities, changes in consumer preferences, and market trends that you may not currently be aware of.”
Question: Please tell me about a recent data analysis project you worked on that was similar to the issues we are interested in.
Explanation: Hopefully, you did your pre-interview research and are familiar with the company’s operations and the challenges they are likely to encounter. The project you describe should be similar to the type of work you will be doing if hired. It’s best to use the STAR method when asked a question such as this: Situation, Task, Action, Result.
Example: “A recent project I worked on involved determining consumer buying habits for products similar to the ones you manufacture. I was tasked with determining what criteria the buyers used to make a decision and how the criteria were ranked. The data set contained over a million individual elements. Using industry-standard methodologies and tools, I was able to determine the key criteria and relate them to the product features. The result of this was the sales and marketing team were able to emphasize the product features consumers used most often to make their decisions. This resulted in a 10% increase in product sales during the next quarter.”
Question: What data analysis tools do you prefer, and why do you like them?
Explanation: This is a technical question geared toward understanding your competencies within the data analysis field. It is looking for specific information and the rationale behind your answer. Technical questions should be answered directly and succinctly with minimal embellishment. Interviewers will ask for additional information if they are interested in learning more.
Example: “Surprisingly, the tool I use most in my data analysis practice is Microsoft Excel. Spreadsheets allows me to easily manipulate and analyze the output from more complex data analysis tools and present it in a format which non-technical stakeholders can easily understand. I also like the ability to create custom formats, formulas, and macros within Excel which make the analysis faster and more efficient. Other tools I use are querying languages such as SAA, R, and Python.”
Question: How do you stay up to date on data analytics tools and methodologies since the field is rapidly evolving?
Explanation: This is both a technical and an operational question. The interviewer wants to make sure your knowledge is current and that you will continue to stay abreast of trends and developments in data analytics if hired. Hopefully, you are already doing this. If so, cite the sources you use to stay current or improve your skills. Also, provide specific names for a few of these.
Example: “Staying abreast of trends in the data analytics field is both challenging and rewarding. I spend about 20% of my time on this activity. Sources I use to stay current in this field include articles, blogs, and industry publications as well as online tutorials, trainings, and videos. Specific sources I use are Venturesity, BizAnalyticsTT, Dataconomy, and the Data Science Institute at Columbia.”
Question: Can you describe some of the practices you use to ensure your data analysis is accurate and the results you are providing can be trusted?
Explanation: This is another technical question which the interviewer is using to confirm your expertise and make sure you will produce results on which they can depend. Specifically, this question refers to the practice of data cleansing. Your answer should address the data-cleansing and data-checking processes.
Example: “Like most data analysts, I use the practice of data cleansing to ensure the results I produce are both accurate and reliable. Data cleansing helps me remove incomplete and inaccurate or irrelevant parts of the dataset. Tools I use to perform data cleansing include Drake, Winpure, Cloudingo, and OpenRefine.”
Question: How do you know you are analyzing the right data for the project to which you have been assigned?
Explanation: While this may sound like an unusual question, it is quite common in business situations. Sometimes, there is a disconnect between what the users are interested in and what the data analyst is working on. By asking this question, the interviewer wants to discover how you go about working with project stakeholders to make sure you are working with the right data set and producing the results they are looking for. The best way to respond to this question is to describe the process you use at the beginning of a project and then discuss your communication style.
Example: “This is an interesting question because I’ve encountered this issue before. Sometimes users don’t communicate their desired outcome for a project or describe the data set they’d like me to use. To avoid this, I schedule a meeting with the project stakeholders before I begin my analysis. We discuss what information they are trying to get, how they plan to use it, and what data set they would like me to use. By doing this, it ensures we’re all on the same page and the results I produce will match their expectations.”
Question: Tell me about a time when you analyzed the wrong data set. How did you discover this, and what did you do to resolve it?
Explanation: This is a follow-up question to the previous question which asked how you know you are working on the right dataset. The assumption is that in every process, errors sometimes occur. If this hasn’t happened to you, then you should state why you were able to avoid it. If it has occurred, describe how you discovered the error and what you did to fix it.
Example: “In my previous position, this exact situation happened to me once. I had completed my initial work on the project and was conducting the first project status meeting with the stakeholders. Their questions and comments led me to believe I was working on the wrong set of data for this project. After some discussion, I confirmed this. I switched data sets and validated with the stakeholders that the new one was what they want me to use. Were it not for the scrum/agile process, the project would have preceded almost through to completion before we had discovered this error.”
Question: What steps clearly communicate the results of a data analysis project to stakeholders who may not have a great deal of technical acumen?
Explanation: Many issues that occur in a business environment are a result of poor communication or misunderstandings. This is especially true when people working on technically oriented projects interface with stakeholders from other parts of the organization. The interviewer asks this question to get a feeling for your communication skills and what steps you take to avoid miscommunication or inaccurate information.
Example: “Clear and accurate communication is the key to any data analysis project. In addition to the initial project planning meeting, I employ the agile/scrum process to provide updates to the project stakeholders on a timely and regular basis. I also make a point not to use highly technical language, acronyms, or anything else nontechnical users may not be familiar with. Finally, I utilize graphs and illustrations whenever possible to summarize the findings of my projects.”
Question: Can you describe your career goals and what you feel would be your next step after this position?
Explanation: When an interviewer asks this type of question, they are trying to determine how ambitious you are and whether the position you are interviewing for is part of your career development plan or just a temporary stop until you find a job you think you should be doing at this point. The best way to respond to this type of question is to describe your career goals and then illustrate how this position fits into your overall plan.
Example: “Fortunately, I developed a specific career plan while still in college. I’ve been working on my career trajectory since then, and so far, I’m right on track. My ultimate career goal is to be a senior leader at an innovative organization focused on data analysis. The position we are discussing will allow me to leverage my experience and the skills I’ve learned so far and prepare me for the next step which is management of a data analysis team.”
Additional Data Analyst Interview Questions
What experience do you have with qualitative data?
How would you define data cleaning?
How do you fix an anomaly or outlier in a dataset?
How often should you retrain a data model?
What is your experience in data reconciliation?
Name a few methods you have used when data cleansing.
Describe some common problems found in data analysis.
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