Why did you choose data science

How do you hire a good data scientist?

If you haven't lived under a rock, you may be familiar with data science making waves across industries. Perhaps you've seen it scrolling aimlessly through Facebook, or you've been actively trying to fill a vacancy in this area. Anyway, data science is an emerging field, making it one of the most desirable job markets of our century.

But with jobs comes a hiring process. With the hiring come interviews with hundreds of candidates. Then you need to analyze, evaluate and search for an employee who is exactly the right person. And this is exactly where the real problem lies: How do you hire a good data scientist?

Fortunately for you, that's what we're going to talk about here. Let's get started!

What do we mean by "data scientist"? '

Before you start inviting new candidates for interviews, make sure you know exactly who data scientists are.

Typically, data scientists excel in the following three areas:

  1. Math and statistics
  2. Machine learning and programming
  3. Business / domain knowledge

Depending on what tasks you give them, you can prioritize the three skills. In most cases, data scientists are well versed in two out of three areas. Those with software and math skills are ideal for tech companies or production roles. On the other hand, those who are proficient in math and other fields usually work as statisticians or scientific researchers. Finally, someone with software and domain knowledge is best suited to data pipelines and business intelligence.

The best thing about it? A professional who can do all 3 is a "unicorn"! While these skills are essential, good communication and problem-solving skills help with performance.

Things to Remember Before Hiring the "Perfect" Data Scientist

Hiring a data scientist is not an easy task. This may be because it is tedious to come up with an accurate job description, or maybe because it is difficult to find someone with the necessary experience and skills.

Make sure you know exactly why you are hiring a data scientist

A good way to accomplish this is to write down all of the business problems and opportunities. It is also important to find out which problem area your data scientist should work on.
Last but not least, you should make sure that you are not biased. A doctorate may sound fancy, but it is not synonymous with experience.

Know what to expect from them

There is no point in wasting time on standard interview questions that don't provide anything essential. Instead, find out what the end product you want to see is. Next, sit down and think about what your chosen candidates should do.
Once you have answered your questions and understand the challenges your data team will face, you can develop a recruitment process that reflects the working conditions in your office.

Make smart decisions about your role in the team

Another great way to ensure that your chosen candidates perform well over the long term is to introduce them to your day-to-day office environment during the interview.
If you do this on that day, your chances of success are higher. Also, make sure your team is both flexible and constantly evolving.

Make sure you provide a supportive product manager

While people love to see scientists trapped in a room, scribbling theories on a blackboard, you only see such a thing in movies.
What your data scientist needs is a team of engineers, stakeholders, and product managers. Product managers are usually amazingly good at handling tasks like customer insights, data analysis, regulatory guidelines, and so on. Although data scientists are involved in these tasks, they will not be able to achieve much without the help of the product manager.

How do you hire a good data scientist?

In case you didn't already know, finding a good data scientist takes a little more than just wishful thinking. In addition, this study has shown that in this highly competitive field, strong candidates receive three or more offers. The success rate of hiring them is therefore less than 50%. We can hear you thinking, "So? Are you going to tell me how the hiring process should go, will you?"
Well, sit back and relax! We're here to make everything easier for you. Let's dive right in!

Switch off your prejudices

The first and most important step in hiring a skilled data scientist is to turn off the nagging voice in your head that is subconsciously judging new candidates.
Since you have no idea about it (that's why it's an unconscious bias), you end up opting for the same type of workers. Letting your bias influence decisions leads to gatekeeping; therefore your office cannot fall back on diverse and fresh talents.

Have a basic version built

Now that you've said goodbye to your subconscious bias, let's move on to the other aspects of the hiring process.
While it's true that data scientists are the perfect way to get your business going, submitting super-tough projects without testing can be your doom. And you don't want that.
Hence, the perfect way to make sure your data scientists are up to the challenge of getting them to fabricate something simple yet creative. This is especially useful for getting senior management to invest in your data team and move on to more challenging projects.

Ask them to build data pipelines

It's no secret: interviews can go from super stressful to downright annoying in seconds, especially if you've been walking in circles for hours asking questions that are of no use to you or your company. Instead of doing that, you can do more hands-on tests.
Your organization's data is not always stored in digital form. And even if they do, there is always the risk that they will be corrupted and inadequately stored. To make sure you have an efficient data pipeline, make sure you hire someone who knows how to collect and combine data from different sources. This can help to drastically improve your data security.

Take a look at her portfolio

There is nothing that makes our eyes sparkle more than when a potential worker shows off some of his most fantastic works. However, it is important to remember that the internet is a huge world of open source forums dedicated to data science. Make sure you know what role they played in making that project in question. When hiring, make sure you hire because of their talent!

Never stop improving your hiring process!

We all agree that none of us will think about our hiring process if it doesn't come "then". Unfortunately, this means that our recruitment process is messy to say the least and will confuse you even more than the candidates.
Instead of spending your Sunday worrying about what questions to ask, you should always have a well-thought-out, flawless hiring process at your service.
This ensures that you are always two seconds away from hiring new talent. Additionally, this ensures that your logs, results, successes, failures, and engagement opportunities are consistent.