10 Smart Interview Questions for Data Analysts (Best Answers Included)
As technology continues its high-speed advance, we’re creating and collecting vast amounts of data every day. This means that data is now a business’ biggest asset. Yet, numbers and statistics can be mind-boggling. With the right data analyst evaluating your numbers, you can target your demographic and proactively make evidence-based decisions, keeping your company ahead of the competition. Here are 10 smart interview questions you should ask when hiring a data analyst for your business.
In recent years, the main challenge has been that while companies were successfully collecting data, they often lacked sufficiently skilled data analysts to access the information and extract insights.
Therefore, it comes as no surprise that data analysts are one of the fastest-growing roles, projected to see a demand spike of 28% by 2020, according to a report by IBM. Indeed, the economist Hal Varian Ronald has defined this role as “the sexiest job of the 21st century.”
While demand for these candidates rises, so does the expectations of them. Data analyst roles now require advanced education and additional skill sets, further driving up demand and salaries. And when it comes to hiring, these positions are now among the most challenging to fill–taking five days longer to find qualified candidates than the market average.
The Right Fit
To start, a general introduction with some basic “getting to know you” questions puts the candidate at ease and it makes the interview flow nicely. These simple questions will give you an insight into their character and personality.
What is a great day at the office?
You want to show an interest in the candidate as an individual and let him or her express the ideal working day in terms of tasks, environment, and collaboration with colleagues. The answer to this question can provide you with key information about how he or she operates and how the candidate will interact with your team. Above all else, the answer should be honest and well-considered.
Describe a situation where you had to use your personal judgment and professional knowledge as a data analyst to resolve an issue.
Asking a candidate to describe a situation, specifically requesting details of both personal and professional inputs, will help you to understand how he or she applies character strengths and technical expertise to find a solution.
Explain how you have handled a difficult situation with a coworker. What was your approach and what was the end result?
Analyzing and interpreting data may technically appear to be black and white. However, the interpretation of data and the communication of its meaning can often lead to conflict in the workplace. Look for an answer that shows diplomacy and self-awareness. Depending on the scenario, a strong candidate will show that she used her knowledge and technical proficiency to stand her ground, or listening skills and empathy to diffuse a conflict situation.
Moving on to the next part of the interview, it’s time to identify whether or not the candidate knows his stuff and has the technical skills required for the role. Moving away from the more personal questions and on to professional ones, you should note whether the candidate is able to talk confidently about his professional experience.
What are the criteria to say whether a developed data model is good or not?
A general data analysis question to start; this shows that regardless of how long the interviewee has been working in her field or how advanced she is in the various types of data mining and modeling, she hasn’t forgotten the fundamentals. As these answers are technical and specific, you are looking for an equally technical and concise response. The candidate should be aware that a developed data model should have predictable performance, adapt easily to any changes in business requirements, and be scalable and easily consumed for actionable results.
With what data analysis software are you experienced?
Not only does this question act as a simple tick-box exercise it also shows how advanced they are in their role and how familiar they are with emerging technologies. All data analysts should be familiar with traditional software applications such as Microsoft Excel, SQL, Python and of course, any particular software prescribed as a mandatory requirement for the role.
How often should you retrain a data model?
Often, when we do things on autopilot, we forget to pay attention to what we’re doing and why we’re doing it. This is another relatively basic yet important question to reveal whether the candidate has forgotten the basics of data analysis. A good data analyst will note how changing business dynamics will affect the efficiency of a predictive model and, therefore, state that the answer to this question is dependent on many variables. However, a strong candidate will go on to provide example scenarios and answers.
Let’s Get Technical
With digital disruption everywhere and data analytics becoming an in-demand position, you want to ensure that after showcasing their current skills that they are passionate enough to grow with the role. You’re looking for a future-thinking mind-set and somebody who is willing to adapt to change.
What’s the most interesting thing you’ve discovered from data?
The answer to this question shows whether or not the candidate is emotionally connected to his role and therefore passionate about it, or whether he is purely there to process the data and leave. Storytelling is a quality that is often overlooked in a good data analysis and showing enthusiasm often means that the candidate is able to effectively communicate data stories with colleagues. The ideal response to this question is less about the answer itself and more about body language. Look for a smiling face, hand gestures, and enthusiastic body language–they will tell you if the candidate is passionate about his work.
What do you think a data analyst role will look like in five years?
The answer here helps you understand whether the analyst is lost in the detail or manages to pop her head up to see the bigger picture. It provides insight into how current she is with the industry and sheds light on her strategic thinking abilities. The interviewee’s response should show she has considered where the industry is headed and how technologies impact her function. A strong candidate will demonstrate business acumen by highlighting what the company will want from their data in five years’ time.
Are there any emerging data analysis technologies you are familiar with but not yet using?
This question combines the candidate’s knowledge of the industry and gives you insight into their views on career progression. More advanced candidates will be familiar with emerging technologies; open-source tools such as Tableau, OpenRefine, Knime; data visualisation tools such as Datawrapper, Qlik, and Solver; and extraction tools such as Octoparse, Mozenda, and Content Grabber. Knowing what is out there could be a reflection of the candidate’s appetite for training.
Wrap it Up
What is the future of big data?
This final theoretical question should start a casual dialogue. The objective is to give the candidate an opportunity to speak candidly. There is no right or wrong answer, merely their opinion. Be sure you leave 10 to 15 minutes for the answer to this question. It is an excellent opportunity to solicit opinions and personal insights from the candidate and close the interview. It is an opportunity for debate, for open thoughts, and sharing ideas.
Of course, there are no right or wrong answers to many of these questions, but you will both be left in agreement that this is an exciting time to be a data analyst.
Looking for a more complete guide on interviewing?
Take a look at our comprehensive guide on How To Interview a Candidate for everything you need to know about getting the best out of any interview, and more interview question templates.