Every business, regardless of industry, is becoming more dependent on the processing and analysis of data.

Thus, it increases the need for new professional positions, such as data scientists, within the organization.

The hiring process might seem straightforward. In the event that a position requires highly specialized skills, hiring becomes much more challenging, especially if you don’t have much experience or knowledge about the position.

As a result, it may be beneficial to plan ‌and study how to conduct the hiring process from beginning to end in advance.

Continue reading if such a scenario applies to you. This article explains how to interview data scientists the right way.

Let’s get right to it.

1. Before starting the hiring process, research the skills you’re looking for and write an appealing job description

Before you start the hiring process, you should clearly know what skills your company is looking for.


So, if you want to be prepared, you need first to do some research. Aside from preparing you for the process, you can also use it to write an accurate job description and attract qualified candidates while avoiding misunderstandings.

In general, data scientists need to possess the following skills:

  • Statistical analysis and computing
  • Machine learning 
  • Deep learning
  • Processing large data sets
  • Data visualization
  • Data wrangling
  • Mathematics
  • Programming

Following the research you conducted previously, you now have all the data and expertise you need to begin the hiring process.

It is now obvious that you need to include them in your job posting. Here is how you might go about it:

  • Company Description. Start your job description by explaining what your company does, relevant accomplishments, and your position in the market. It is a good idea not to overstate the positive aspects of your business.
  • A description of the job requirements. In this section, be sure to include everything you’re looking for. Outline the necessary years of experience, skills in data management, degree type (if applicable), and other technical skills for the job.
  • Job Duties. In this section, you will describe in more detail what the candidate will do after accepting the position and joining your company. Include information about what the candidate’s daily responsibilities are and who will be referred to by the candidate.
  • List of Desired Soft Skills. In contrast to technical skills, soft skills are more important to excel in the workplace and collaborate with others. Examples include communication, flexibility, and problem-solving abilities.

2. Use remote hiring software

When you’re hiring remotely, you might need the right tools to make sure the process goes smoothly.

By using certain tools, like remote hiring software, you can manage the entire hiring process from beginning to end.

When you own a big company that has different positions open and receives tens of thousands of resumes, handling all of this manually can be quite challenging and labor-intensive, if not impossible.

It is possible, for example, to use some software that automatically extracts information from CVs, inserts it into a database, and scans and identifies the candidates who are a better fit for your opening.

Apart from this, there are many other remote hiring software and tools available that simplify a number of processes and tasks.

3. Conduct a data science hiring assessment

Especially if you lack experience or knowledge of the position you’re hiring for, it might be difficult for you to evaluate candidates effectively.

Fortunately, there are tools today that can simplify this process, as well as facilitate the evaluation of candidates.

Software like TestGorilla, for instance, offer tests such as the data science hiring assessment, which focuses on the knowledge and qualifications of data scientists.

Following the completion of the tests, the system ranks the candidates based on their highest to lowest scores.

Therefore, you will be able to quickly identify the top performers for the test and select them to continue the interview process.

4. Prepare in advance the questions for the interview

Interviewing a candidate with high levels of knowledge and experience without being prepared can be a challenge.

To avoid embarrassing moments of silence or look unprofessional by sounding unprepared, you should prepare yourself in advance in such a situation.

It is therefore necessary to prepare all the questions you may ask during the interview, as well as the answers you should expect the candidate to give you.

The following are examples of questions you may want to ask a data scientist during an interview:

  • What makes you want to work as a data scientist at this company?
  • How did your previous work experiences prepare you for a role as a data scientist?
  • What strategies do you use to overcome professional challenges?
  • How will you use tools and devices in your role as a data scientist?
  • What is selection bias, and why do you need to avoid it?
  • What are the best practices for organizing large sets of data?
  • Is it always better to have a large amount of data?
  • How does root cause analysis work?
  • What is a typical method for identifying outliers within a data set?

After you identify the questions that are relevant to your company and the position you are hiring for, make a note of them and use them for the interview with the candidates.

5. Real time software testing interview questions

Technology advances have resulted in companies seeking innovative ways to conduct first-approach interviews with candidates, saving them time and effort otherwise spent on candidates who are not a good match.

One of such innovative ways involves the use of real-time software testing interview questions. Software of this kind involves posing questions to candidates and requiring them to answer them in real-time by recording themselves either on camera or through audio recording.

Depending on the software, you can review all the answers or the software will do it for you, thereby speeding up and facilitating the hiring process.

6. Involve other members of your team in the interview

Especially if you have to choose from several good candidates, the decision can be overwhelming, particularly if you’re doing it alone.

In this case, it might be helpful to get the opinions of other team members and involve them in the hiring process.

In order to accomplish this, it is best to conduct a multi-step process, in which each step involves different employees of your company. As a result, everyone will have an opinion and the decision will fall on the candidate the majority considers to be the most suited to the role.

As a result, you’ll be able to identify the perfect fit for your company more easily and quickly, preventing you from feeling overwhelmed and unsure about what to do.

7. Conduct a real-time practical test

By conducting a real-time test, you can eliminate any doubts about whether or not candidates are lying about their knowledge and skills.

The tests are usually carried out in front of your eyes as part of a normal interview, and they have to be solved within a certain time limit you set.

During these tests, you’ll be able to see the candidate’s work habits, their efficiency in executing tasks, and their behavior under pressure.

There are a lot of software programs available today that offer all the tools you need to perform these tests.

8. Test candidates with a real-life example of a project

After the interview, if you are still unsure about which candidate, among the best ones, to hire for the role of data scientist, you might want to take another final step.

If you want to be sure that the candidate is up to the task, then you can have them work on a real-life example of a project.

Make them solve a problem they may come across every day or from time to time while working for your company, and give them a deadline by which they must complete the task.

By doing so, you will be able to identify the candidate who has solved the project or task in the most efficient manner and within the shortest period of time by following this way.

Conclusions

Here is the end of this article on how to interview data scientists.

As we have seen, even if you lack data science skills or knowledge, there are other methods today that can help you hire the right candidates in the most seamless way.

Data science hiring assessments and the use of remote hiring software are just two examples of valid measures.

It is up to you to decide which method to use based on your needs, preferences, and the availability of your company.

Thank you for taking the time to read this blog post. We hope it was informative and helpful to you.

If you want to read more, check out this article on how to interview.

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