Data Analysts help companies by collecting and analyzing data on various business topics to generate insights that inform others to make decisions that optimize the business. Data Analysts are often involved with the entire lifecycle of data including acquiring data, creating systems for storing and managing data (e.g., databases), analyzing and interpreting data, and synthesizing and reporting results to advise others. They typically use their technical skills in quantitative statistical analysis, basic programming languages (e.g., R, python), and data reporting to enhance the performance of a specific team or department (e.g., marketing, sales, customer success). They do so by using past data to draw insights and create visualizations to communicate a story about what has happened.
Core skills for Data Analysts
Quantitative Data Analysis
How to interview Data Analysts effectively
While it might seem difficult to figure out whether a candidate will succeed as a Data Analyst in your company, a well-developed set of interview questions that tap into the core skills required to perform in a Data Analyst role will go a long way in helping you decide.
But where do you start? How do you develop a set of great interview questions?
The best interview questions come directly from a job analysis. A job analysis is an evidence-based method that focuses on assessing key features of a particular role. These features describe both the job itself (i.e., tasks, responsibilities, and performance objectives), and the characteristics required of someone to perform successfully in the job (e.g., knowledge, skills, and abilities). A job analysis forms the basis of many HR practices such as compensation, performance management, and - you guessed it - how to interview and hire candidates.
At Hireguide, we’ve done the job analysis work for you. We’ve used the method to identify a core set of skills associated with the Data Analyst role, and we’ve developed and validated a list of behavioral and situational questions with answer guides that tap directly into those core skills. And that’s not all. We’ve compiled these questions and created a Data Analyst Interview Template for you that integrates other interviewing best practices. Skills-based interviews will not only help you make higher quality and evidence-based hiring decisions, but research also shows they enhance fairness and reduce bias in your hiring process.
Example questions to ask
Imagine you are working on preparing and cleaning a dataset for analysis. How would you detect and deal with outliers?
- Explains outlier detection methods (e.g. univariate, multivariate, Minkowski, etc.)
- Discusses different ways to deal with outliers (remove, transform data, etc.)
- Elaborates on important considerations to make when deciding on a solution
- Considers analyzing data both with and without outliers to understand impact on results
- Shares any learnings or best practices from past experience
Describe a time you faced an unexpected problem when analyzing data. How did you handle it, and what were some key takeaways from the experience?
- Clearly describes the situation and how they identified the problem
- Considered the root cause of the problem to propose an effective solution
- Discusses solutions they considered and justifies their choice
- Considers implications of the problem on the quality of the analysis/results
- Share learnings and best practices to prevent the issue reoccurring