10 Analytical Interview Questions for Data Science Roles
Analytics skills are part and parcel of the data science process. Anyone working on a data science or advanced analytics team must demonstrate intellectual curiosity, comfort with uncertainty and an ability to apply rational critical thinking to solve problems.
So what types of questions might you ask to assess these traits?
We’ve put together a list of 10 example questions:
1. Tell me about a time when you had multiple important projects to finish and how you prioritized them.
This question provides an overview as to how a candidate weighs different factors and information, their approach to analyzing them to determine priorities and outcomes.
2. Imagine a situation in which a teammate wants to solve a problem in a certain way, but your boss has a very different approach in mind. Your colleague comes to you asking for help in deciding on the right approach. What do you do?
This question examines multi-layered analytical thinking. The candidate must weigh a number of possible factors and outcomes and do a bit of scenario analysis at a technical, professional and business impact level.
3. What do you think are the criteria to say whether a developed data model is good or not?
This question combines a bit of analytical thinking as it would apply to the job at hand allowing you to assess technical skills as well.
4. When do you think you should retrain a model? Is it dependent on the data?
As with the previous question, this open-ended question will give you insights into 0n-the-job critical thinking and associated decision-making skills.
5. How do you identify a barrier to performance?
This simple question reveals how a candidate would approach a real-world problem on the job. It will also give you insight as to how a candidate defines personally what a challenging situation is.
6. How do you clean up and organize large datasets?
The answer to this question will reveal a candidate’s ability to organize and think about an approach to work based on their knowledge and judgment of what it will take to analyze data and information accurately and meaningfully.
7. Why are you interested in analytics?
The answer to this question will likely reveal the building blocks of a candidate’s approach to problem-solving and critical thinking and how far they are willing to go to solve problems.
8. How would you come up with a solution to identify plagiarism?
This kind of question will give you an insight both into technical ability and a candidate’s ability to use those skills to solve an open-ended problem.
9. What are the steps in a typical analytics project?
This question won’t necessarily give you deep insight into a candidate’s thought process, but it will allow you to evaluate if they have a process at all. You can ask further questions with some of the steps they enumerate to gauge analytical skills.
10. Provide a real-world challenge from your company and ask the candidate to solve it.
There’s nothing more revealing about a candidate’s analytical thought process then observing how they apply it to a real-world situation, especially one that impacts your company. For this reason, real-world challenges are core to QuantHub’s platform.