What Questions Should You Ask at Your Data Scientist Interview?



Data collection is a central concern for pretty much every business, so the demand for skilled people to fill Data Scientist jobs and make use of this information is high. Companies need data experts who can organise the collected information and extract valuable business insights.

When hiring for Data Science roles, companies are looking for the trifecta of strong business acumen, technical expertise, and a mathematical mind fluent in figures. 

The interview process not only enables the employer to locate the right candidate for the job, it also helps you ascertain whether this role and this company is the right fit for you, so use the time wisely to ask questions that will help you make an educated decision.

Who will I be working with?

Simple enough. This question aims to find out the relationship status of Data Science in relation to the rest of the business. Working in Data Science involves working across various departments and educating your colleagues on the impact and importance of data to their own outcomes. Hiring managers are looking for people with great communication skills and a proven track record of engaging and working well with others.

Who in the organisation specifically will benefit from my work?

What are the challenges that my work will be helping to solve for the business?

Does the company encourage cross-collaboration across the business so that the insights made by the Data Scientists can make a real difference?

For the interviewer, these are the types of questions that show you are serious about working in Data Science with the goal of tackling real problems. For you, they will dig into exactly how the business views and supports the Data Science function and who you will be liaising with a lot of the time.

You can follow these up with:

What is the investment into Data Science? Is it supported by the whole company?

Here you want to determine how the company views the data science function. As a relatively new role within a lot of businesses, it’s important for you to understand what the company has set up in terms of team, tools, processes and how Data Science interacts with other elements of the business. This is also your chance to ascertain the type of access you’ll have to key business stakeholders and C-Suite level. How invested are the company in Data Science and how will they be supporting you? You could then ask about the tenure of those working in technical roles to gain further understanding of company culture and how many of your fellow data professionals are contracting versus full time.

What do you expect to see from me in the first 6 months?

This is a clear setting of expectations, both for you and the business. It’s smart because it shows the company that you are keen to impress and do well by building that foundation early on. You want to understand what they consider to be important which further demonstrates your cultural values are aligned with theirs. For you of course it gives you a clear set of parameters within which to hit the ground running.

How will my projects further the goals of the business?

The best data science solutions are generated from a clear understanding of the needs of the business and a deep understanding of the data. So, asking a question like this, further to having demonstrated your enthusiasm for the company and the research you’ve done in preparation for the interview, reinforces that you understand what you’re being hired to do.

How is data collected at this organisation? Are you using open-source technologies or proprietary software?

These kinds of questions are really important for you to see how committed the business is to technology and the quality of the data you’ll be working with.

You may also want to ask where the business is on their data journey.

Here you are ascertaining whether the business is familiar with AI (Artificial Intelligence), ML (Machine Learning), predictive analytics and the like. You want to find out how advanced they are or whether they’re still at the data manipulation and data wrangling phase.

The key thing hiring managers are ideally looking for when it comes to filling Data Science jobs is good communicators who can easily explain the problem and its solution in a way that their non-technical colleagues can understand. Furthermore, they want someone who can align their projects with what the company is trying to do and demonstrate an understanding of what the company is trying to achieve.


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