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How to hire a good data scientist?

How to hire a good data scientist?

Unless you've been living under a rock, you may be familiar with the data science field making waves in different industries. Maybe you saw it while scrolling aimlessly through Facebook, or you've actively trying to look for a job in the field. Either way, data science is an emerging field, making it one of the most sought after jobs in our century, and everyone knows about it.

But with jobs comes a hiring process. With hiring comes interviewing hundreds of candidates. Then, you need to analyze, assess, and look for an employee who's just right. And that's where the real problem arises: how do you hire a good data scientist? 

Lucky for you, that's what we're going to discuss here. Let's get started!

What Do We Mean By 'Data Scientist?'

Before you start inviting new candidates to interview, let's make sure you know who data scientists are exactly. 

Typically data scientists excel in the following three fields:

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

Depending on what tasks you provide them with, you can prioritize the three skills. More often than not, data scientists are adept in two of three areas. Those with software and mathematical skills are ideal matches for tech companies or production roles. On the other hand, those proficient in maths and domains typically work as statisticians or scientific researchers. Lastly, someone with software and domain skills performs best in data pipelines and business intelligence. 

The best part? A professional with mastery in all 3 is a 'unicorn!' While these skills are essential, good communication and problem-solving abilities help with performance. 

Things To Remember Before Hiring The 'Perfect' Data Scientist

Hiring a data scientist is no easy task. This may be because it is ridiculously exasperating to develop an accurate job description or maybe because it's difficult to find someone who has the required experience and skills. 

Make Sure You Know Exactly Why You're Hiring A Data Scientist 

A good way to go about this is by noting down whatever business problems and opportunities. Besides that, it's essential to work out what problem space you want your data scientist to be working in.

Last but not least, make sure you're not biased. While a Ph.D. sounds fancy, it doesn't equate experience. 

Know What You Want Them To Do

It's no use wasting time on standard interviewing questions that provide nothing substantial. Instead, figure out what the end-product you want to see. Next, sit and think about what you want your selected candidates to do. 

Once you've answered your questions and know what challenges you want your data science team to face, you'll be able to craft a hiring process that reflects your office's working conditions. 

 Make Smart Decisions Know Where They Fit In The Team

Another great way of ensuring whether your selected candidates will do great long-term is to introduce them to your day-to-day office environment during the interview.

If they do so on that day, the chances of them succeeding are higher. Besides, make sure your team is both flexible and always evolving.

Ensure You Provide A Supporting Product Manager

While people love to see scientists locked in one room, scribbling theories on a blackboard, you only see such a sight in movies. 

What your data scientist needs is a team of engineers, businesses, stakeholders, and product managers. Product managers are typically amazing at taking care of tasks like customer insights, data analysis, legal guidelines, etc. While data scientists are involved in these, they won't be able to do much without the product manager's help. 

How To Hire A Good Data Scientist?

If you haven't already figured it out: finding a good data scientist requires a little more than wishful thinking. Moreover, the study showed that in this super competitive field, strong candidates receive three or more offers. Thus, the success rate of hiring them is less than 50%. We can hear you thinking: 'so? Are you gonna tell me how to do the hiring process, right?' 

Well, just sit back and relax! We're here to make everything easier for you. Let's dive right in! 

Switch Of Your Unconscious Bias

The first and foremost step of hiring a proficient data scientist is to turn off that nagging voice in your head that subconsciously judges new candidates.  

Since you have no clue about this (that's why it's unconscious bias), you end up choosing the same kind of workers. Letting your biases influence decisions leads to gatekeeping; thus, your office cannot reach out to diverse and fresher talent.

Get A Basic Version Built 

Now that you've said goodbye to your unconscious bias let's move onto the other aspects of the hiring process. 

While it's true data sciences are the perfect way to boost your business, handing out super tough projects without testing can mean your downfall. And you don't want that. 

Therefore, the perfect way to ensure your data scientist is up to mark, get them to fabricate something easy yet creative. This is especially useful to get higher management to invest in your data science team and move onto more challenging projects. 

Ask Them To Build Data-Pipelines

It's no secret: interviews can vary from being super stressful to straight-up annoying in a matter of seconds, especially if you run in circles asking questions for hours on end that are of no use to you nor your company. Instead of doing that, you can carry out more practical tests. 

Your organization's data is not always stored in digital format. And even if it is, there are always chances of it corrupting and being inadequately stored. To ensure you have an efficient data-pipeline make sure you hire someone proficient in collecting and combining data from multiple sources. This can help drastically improve your data security. 

 Look Into Their Portfolio

There's nothing that makes our eyes sparkle more than when a possible worker shows some of their most fantastic works. However, it is important to remember the internet is a vast world of open-source data science forums.

Make sure you know what part they played in fabricating said project. When hiring, make sure you hire for their talent!

 Never Stop Improving Your Hiring Process!

We can all agree that none of us think about our hiring process unless it comes to 'that' moment. Unfortunately, this means that our hiring process is chaotic, to say the least, and confuses you more than the candidates. 

Instead of spending your Sunday worrying about what questions you should ask, you should always have a well-thought-out, flawless hiring process at your service. 

This helps make sure you're always two seconds away from hiring new talent. Furthermore, this ensures your protocols, results, success, failures, and engagement opportunities are consistent.