Why this matters:

Data analysts work with a variety of different tools and programs, and new ones are rolled out every year. While experiences may vary, what’s most important is their ability to learn and adapt, as this will help your company stay on the cutting edge of data analysis.

What to listen for:

  • Knowledge of relevant data languages, such as SQL
  • Understanding of relevant database concepts and business intelligence tools
  • Willingness to learn new software and tools if necessary

Why this matters:

While every interviewee will hopefully research your company thoroughly before speaking with you, a top data analyst also knows how to ask good questions to understand the business’s growth needs. This question can also provide a window into the sort of projects they’d be eager and able to tackle for your company if hired.

What to listen for:

  • Curiosity, resourcefulness, and familiarity with your company’s goals
  • Knowledge of processes used in performance data analysis
  • A business mindset focused on replicating best practices and identifying opportunities

Why this matters:

Data cleaning is an essential process that enhances the quality of data. Top data analysts understand this and never skip a step. When unclean data is used for analysis, it can lead to misleading results and wasted time, which is why data analysts must ensure the integrity of all data they use for analysis purposes.

What to listen for:

  • Knowledge of best practices, such as sorting data by attribute
  • Experience breaking down a large dataset to increase iteration speed
  • The ability to clearly articulate why particular practices are preferable

Why this matters:

A data analyst with good “data sense” can look at a chart or table and sense that something is off — say, a conversion rate that’s too low, or a booking number that seems wrong. Untangling data issues like this can come from experience, but also from problem-solving abilities and a deep understanding of statistics, business, and economics.

What to listen for:

  • Relevant experience proactively identifying data inconsistencies
  • Understanding of how to work through appropriate channels to solve an issue
  • Data savviness and strong problem-solving skills

Why this matters:

Having the candidate talk you through a large-scale assignment will give you good insight into their overall experience level as a data analyst. If they’ve taken a project from conception to actionable results — and worked through complex data challenges to get there — then this is an experienced data analyst worth moving to the next round.

What to listen for:

  • Indication that the candidate has a strong iterative process for tackling challenges
  • Willingness to accept feedback from the stakeholders and adapt to changes
  • Leadership experience seeing a project through from start to finish

Why this matters:

Data analysts will often conduct experiments and A/B tests to determine the potential success of a new feature or campaign. Most critically, analysts use data experiments to shape company strategy and produce better results. Depending on the candidate’s level of experience, they may not have conducted advanced experiments, but should understand the logic behind them.

What to listen for:

  • Sensible explanation as to why experiments are conducted
  • Description of metrics used to track and quantify results
  • Definitions of success that align with company values, goals, and interests

Why this matters:

Great data analysts rely on their soft skills as much as their technical abilities. This question can help you assess which soft skills candidates value most in others — and how they see themselves. This will give you a good sense of how they’ll fit in with the rest of the team and whether they’ll bring something new to the table.

What to listen for:

  • Recognition of the importance of a well-rounded analyst above and beyond math skills
  • Self-assessed strengths in problem-solving and analytical thinking
  • Experience working on a team and the ability to get along well with others

Why this matters:

Since data analysts work with staff with varying levels of data fluency, you need to know they can communicate effectively. This is a role that often requires working directly with management, engineers, and end users to gather assignments and requirements, provide detailed status updates for large data projects, and build communication bridges across departments.

What to listen for:

  • Signs that the candidate is passionate about helping others understand data
  • Communication skills in expressing complex ideas clearly
  • Organizational abilities to deliver data in an engaging, easy-to-read format

Why this matters:

Asking this question can help you spot candidates with passion and ambition. It can also help you understand where their interest lies and whether the role will be fulfilling for them. If they are deeply passionate about data, and your company can offer the kind of analysis opportunities that they crave, they’re likely to thrive in the role.

What to listen for:

  • Genuine interest in statistics, economics, logic, and reasoning
  • A personal anecdote describing how an interest in data analysis first formed
  • Knowledge of recent developments in the field, such as artificial intelligence
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