Hiring a top data analyst for your company is a big responsibility. After you’ve written the job description and vetted the applications, the next step is to interview applicants and evaluate their hard, soft, and technical skills and personality to find the right fit for your company. Asking the right questions can give you measured insights into your candidates and help you choose an experienced data analyst who will excel at your company.
Revelo simplifies this process by helping you source talent and line up interviews. We can even coach you through the interview process to make hiring as seamless as possible for your company. Of course, you still need to be in the room, asking the hard questions. This article provides critical questions that can help you evaluate entry-, mid-, and senior-level data analysts to find the right fit for your organization.
What Is a Data Analyst?
Data analysts collect, organize, and model data to help decision-makers reach data-supported conclusions. Although they are similar to data scientists, data analysts specifically work with structured data sets to solve business problems in the here and now. Alternatively, data scientists work with less structured data to make predictions about the future. Data analysts must understand how to spot trends in data and present their findings in an understandable way so businesses can make decisions quickly and effectively.
Hiring a data analyst allows you to use data more thoroughly and in many ways, so you may wish to hire one if you’ve started collecting insights from data into customer behavior but find it challenging to keep up with the wide breadth of information. Revelo can help, starting with some relevant analyst interview questions and answers.
Entry-Level Data Analyst Interview Questions
Entry-level data analysts should be familiar with programming languages like Python and R. They should also know how to clean and model data. Generally, entry-level data analysts will work on a larger team. Consider hiring a highly coachable candidate for the data analyst role, so your team can eventually help them move up through the ranks.
Below are some interview questions for data analysts with minimal experience.
What is data cleansing?
Entry-level applicants need to prove that they understand the scope of the job. They should be able to explain that data cleaning means removing any inaccurate, improperly formatted, or corrupted data from a data set before beginning the analysis process.
What are the most important ethical considerations to remember as a data analyst?
Although entry-level data analysts aren’t expected to know everything, you will want to ensure they know how to collect data legally and ethically before hiring them. Some of the ethical considerations your entry-level candidate should be able to mention the following:
- Getting informed consent before collecting personal data
- Keeping collected data private and secure
- Paying attention to potential biases during the data collection process and ensuring methods for collecting data aren’t unduly influenced by these biases
- Ensuring collected data is complete, accurate, and reliable
What would you do if asked to analyze a complex data set outside of your skillset?
The best entry-level candidates are highly coachable. With this question, you’re looking for applicants who can admit when a data set is outside their skill set and ask for help learning a new skill rather than candidates who would attempt to analyze data they can’t handle independently.
Mid-Level Data Analyst Interview Questions
Mid-level data analysts also need to be comfortable with programming languages and modeling data and, at this stage, able to fully interpret data and reasonably present their findings. Additionally, mid-level data analysts may occasionally need to step in for senior-level analysts if they’re away from the office, so you will want a candidate with strong communication skills and flexibility.
Below are several questions to ask a mid-level data analyst.
What’s the difference between data mining and data profiling?
Data mining is the process of looking for new information that hasn’t been used before and converting raw data into usable data sets. Data profiling, on the other hand, evaluates existing data sets for logic and consistency. Mid-level data analysts must be able to handle both types of data processing and should have an understanding of the difference between the two.
What’s the difference between a treemap and a heatmap in Tableau?
Mid-level data analysts should be familiar with presenting data in various ways. Tableau is one of the more commonly used pieces of data presentation software; knowing the difference between its types of visualizations shows that your candidate is equipped to present information in various ways.
In this case, you’re looking for a candidate who can explain that a treemap displays information in a selection of nested, colored rainbows, where dimensions create the structure of the treemap, and measures define the size of the actual rectangles. On the other hand, looks like a text table, but different colors and text sizes indicate different values.
What’s your data analysis process when you start working with a new data set?
Mid-level applicants should have experience working with data. By asking this question, you’re looking to ensure that they can logically explain their process using terms that non-technical personnel can understand. This is a good way to ensure they have the communication skills to explain their technical work at a non-technical level. You’re also looking to ensure they understand how to clean and analyze data and use that data to solve problems; both aspects of the job should be addressed when candidates answer this question.
Senior-Level Data Analyst Interview Questions
Senior-level data analysts should be experts in the field of data analytics. In addition to ensuring they have a strong grasp of programming languages and strong communication skills, you’ll want to look for someone with strong leadership qualities. Often, your senior-level data analyst will need to coach junior-level analysts, oversee data analysis, assess what data analytics software and data analysis tools to utilize, and deal with the most challenging problems your company is facing. They need to work well under pressure and have strong organizational skills to keep up with an ever-fluctuating set of priorities.
Below are several questions an interviewer may ask a senior data analytics professional.
Walk me through your data preparation process when presenting to key stakeholders with no technical knowledge.
Senior-level data analysts are often in charge of presenting data that’s been analyzed by the team in a way that non-technical stakeholders can understand. With this question, you’re looking to see which presentation tools commonly used by data analysts your candidate is most comfortable with and what strategies they have for communicating technical data to a non-technical audience.
By asking them to explain the process, you will get a real-time example of their communication skills and ability to break down a technical process into understandable steps.
Imagine yourself in charge of a team of three analysts: yourself, a mid-level analyst, and an entry-level analyst. You also have three data sets that need to be analyzed. One data set looks at the types of purchases made based on the time of year. One data set looks at the ages of customers. One data set looks at your company's profits and expenditures. Which set do you keep for yourself, and which sets do you ask each of your team members to analyze?
This question is a real-world example of the type of problem your senior-level data analysts will face daily. By this stage in data analysis, senior-level candidates should be able to recognize that the data sets are examples of univariate, bivariate, and multivariate data sets. Ideally, you’ll want a candidate who gives the univariate example — the customer ages — to their entry-level team member, gives the bivariate example — purchases vs. time of year — to their mid-level team member, and keeps the multivariate problem of profits and expenditures for themselves.
You’ll also want to look out for candidates who say they’d try to handle all three data sets themselves. This is a sign that they’re not yet prepared for what it takes to be in charge of a team; their inability to delegate tasks could cause them to burn out further down the road.
What was your most challenging data analysis problem, and how did you solve it?
This question helps you ensure that your senior-level candidate has faced the challenges your company is liable to present them with. Although there’s no one right or wrong answer, an ideal candidate will have an answer and a clear explanation for how they addressed the problem when it arose.
Hire a Data Analyst With Revelo
Hiring a qualified data analyst can be a difficult task, especially if you don't understand data analysis and its nuances yourself. It requires sifting through numerous applications, sourcing and vetting them, and then going through an arduous hiring process to find one with the relevant hard and soft skills to do the job and the right personality to mesh with your company.
Luckily, Revelo can help. We match companies with pre-vetted, highly qualified applicants who have already proven that they have knowledge of data analysis and the hard and soft skills to get the job done. We even help with administrative tasks like managing payroll, benefits administration, taxes, and local compliance adherence, all to make the hiring process as seamless as possible.
Contact us to learn more about common interview questions that can help you assess candidates' experience with work as a data analyst and to start hiring top data analysts for your team today.
