If you're preparing for an interview for a data analyst role, there are specific questions about data analysis you should prepare answers for in advance. But there will inevitably be questions that you cannot predict, so it's also a good idea to do your research about the company you've applied to. By following this advice and preparing in advance, you will be ready to answer any data analyst interview questions that come your way.
Having an idea of what data analyst interview questions to expect can make the interview easier, so let's look at some of the most common data analyst interview questions an interviewer might ask. Then, you can land that data analysis job you've always wanted.
This is one of those questions that you can expect to come up in nearly every job interview, not just in data analyst interview questions. Employers want to hire someone who is enthusiastic not just about the job itself, but the company as a whole. As a data analyst, you might find an opportunity to work for a start-up, in which case your interest in the growth and success of the company will be even more important.
So what's the best way to answer this question? Research. Search online for information about the company.
Or better yet, visit their website to learn more about their values and their company ethos. You could answer by saying what you admire about the company and their stated mission, and why this makes them a more attractive employer over their competitors.
If you're passionate about data analytics, you might think that this is the easiest question to answer. But it is still worth preparing an answer in advance.
It's easy to fall victim to job interview nerves and forget what you want to say, and this is certainly one of the data analyst interview questions you don't want to appear stuck on. An interviewer will ask this question to check your understanding of data analytics and whether you fit their criteria.
Your answer to this question should be relevant to the data analyst role and should express your enthusiasm about the various areas related to data analysis: statistics, data mining, data profiling, processing raw data, data sets, and big data, and whatever else inspires you the most about the job.
You should also take this opportunity to link these aspects of data analytics to your own skills, such as problem solving, critical thinking, and creativity. This will show them that you have a nuanced understanding of what is expected of a data analyst and that you possess the different types of technical and soft skills they need.
It's also worth remembering that data analyst interview questions tend to build from the answers you give. So if you mention your proficiency in problem solving, you will be expected to answer questions that test your critical thinking and thought process.
Fermi problems are a favorite with interviewers when questioning candidates for data analyst roles. This is one of the data analyst interview questions you should expect.
Interviewers will ask situational questions like this to potential data analysts assess your approach to a difficult problem and how you went about solving it. By asking about a difficult situation in the past, they are better able to predict how you will behave in the future when faced with similar data analysis issues. If your answer is unsatisfactory, they might see this as a reason pass on hiring you as a data analyst.
But don't panic if you get asked questions like these. If you think about similar questions and answers in advance, you can shape your answer based on the specific data analyst interview questions and answers they might ask and expect to hear.
The most important thing to do when answering these different types of data analyst questions in the interview process is to mention the soft skills you used in the situation and what you have learned from it. For example, you might describe a time when you were given a project that you had never encountered before (difficulty), and in order to remedy the situation you had to explain this to your supervisor (communication skills), after which they assigned a more experienced colleague to oversee your work which helped you complete the project successfully and get great results (learning experience).
For an employer, this would indicate that you are honest and upfront, that you can learn on your feet, and — most importantly — that you can be trusted with a challenging data analysis project.
As another example, if you were working on a data model that involved machine learning or particular data mining algorithms, describe your thought process and how you used your data sources to gain the insight need to complete the task. Be detailed and show your knowledge and software experience as a current or aspiring data scientist.
This is an opportunity for you to discuss your competence as a data analyst and your technical skills. Pay attention to the job description and check to see if it mentions a specific type of software. If you are well versed in several types of data analysis software then make sure to communicate your varied experience to the interviewer, while focusing on the specific software the company uses.
For example, if the company lists Power BI as their preferred software then your response to the could be something like: "I have experience with several types of software including Microsoft Excel and Tableau for data cleansing and data visualization, but I am most proficient in Power BI and using it to provide actionable insights for business decisions".
Now that you know some of the most common questions you could be asked in a data-analyst interview, you can prepare your answers in advance and go into it with confidence. Other tips for preparing for an interview are to think about how you organized and approached past projects as a data analyst.
Be ready to answer any technical questions about data analytics, such as being asked to explain the difference between data mining and data profiling, to explain time series analysis, data validation methods, KNN imputation method, and how to manage large data sets. Also be prepared to talk about your process when beginning a new analytics project and your personal work style.
With all the necessary interview preparation done, you will on your way to securing a job as a data analyst.