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How to Hire Data Scientists and Data Analysts

Recruiting for data roles has become extremely difficult. From a scarcity of qualified talent to time consuming assessments, the hurdles are endless. In this article, we'll go through the current state of hiring for data roles and how DataCamp can help your business hire better!
May 2022  · 7 min read

DataCamp Recruit - Simplify how managers find and hire data talent

It’s not breaking news that data roles are in huge demand. Plenty of stats show how the market is growing and will continue to grow. Research firm Fortune Business Insights predicts the global big data analytics market will grow to $549.7 billion in 2028. With an expanding data market comes an expanding need for employees and expertise in the space. Since 2016, there has been a 480% increase in data science jobs available, with demand from top industries including Finance, Healthcare, Sharing Economy Services, and even Entertainment. Despite the glut of data jobs available, as of 2020, there has been a shortage of 250,000 data science professionals. Why? Because it’s difficult to find and hire qualified talent. This guide explains why that is, and how DataCamp can help your business hire better. 

Interested in speaking with one of our experts? Use this link to book a free demo today. 

Why is it so hard to hire data scientists? 

Amongst the many difficulties companies face when hiring data scientists and analysts, there are three overriding trends: the unmatched supply and demand for jobs, lack of specificity around data science jobs, and an unsuitable hiring process. The problem fundamentally comes down to three factors. 

1. Demand for data talent 

First of all, the demand for data talent far outstrips the supply of qualified candidates. This problem trickles down and catalyzes many of the issues in the data hiring process. It’s a simple supply and demand issue: there aren’t enough candidates to match the ever increasing amount of data jobs available. There is however a lot of interest and hype being generated around data jobs. For instance, data scientists ranked third on Glassdoor’s “50 Best Jobs in America for 2022” list, and incentives such as high salaries (between $75,000-120,000 on average for data analysts and scientists) have piqued the interest of many. However, this is creating our next problem: companies are choosing from candidates interested in the role, but not necessarily the right kind of candidates for data science. Quantity over quality. 

2. Unspecific job adverts

So now companies are picking from a large pool of applicants, many unsuited to the role at hand. But is the role being advertised correctly? Oftentimes, no. Unspecific advertising attracts a likewise set of applications. Why does this keep happening? Job posts are often vague about these data roles because the company behind them doesn’t fully understand what data science is, and cannot differentiate between the different roles and their requirements. There is still a lot of ambiguity around data science, what kind of jobs it includes, and what kind of experience or skills are needed to meet the role. Hiring managers and recruiters must look for the right combination of tech and business skills required of analysts and scientists respectively. Without a proper understanding of the roles they’re hiring for, how can businesses hire the best data teams? 

3. Unsuitable hiring process

Without a fundamental understanding of data science, the hiring process often misses the mark. For starters, companies are still using LinkedIn messenger and other messaging platforms as their primary tool to access candidates. Whilst this is a common route to headhunt potential employees, it’s not the most effective for scouting data scientists. With so many roles to fill, candidates are swamped with similar messages, and the chances of your business standing out amongst these reach-outs are unlikely. 


This leads us to the next problem at hand: hiring managers don’t know how to evaluate data scientists. Quantifying experience in data science is not as straightforward as it may seem, and hiring managers are routinely focusing on one type of skill and not the other. Academic background is being revered over hands-on experience. Science and math skills are focused on, whilst problem-solving and soft skills, including business acumen, client management, and data storytelling, are overlooked. These experiences and skills are crucial to data science, however are being neglected in the selection process. This also means that senior candidates are not being distinguished from those with much less experience. 

How can we fix this? 

These problems may seem overwhelming, but DataCamp can help simplify the recruitment process for your business. We know that recruiting for data roles can be confusing and time-consuming, which is why we launched DataCamp Recruit. 

1. Specialize in Data

DataCamp Recruit is a platform built to help you recruit for data roles. Of course, there are plenty of recruitment platforms out there, including LinkedIn, Indeed, and Google For Jobs. But what makes DataCamp Recruit special? DataCamp’s platform focuses on data roles only, bypassing the hunt for unsuitable candidates. DataCamp Recruit gives you access to the candidates you’re looking for: data scientists and analysts. 

2. Access to job-ready candidates 

The selection process is already streamlined for you. Not only does DataCamp recruit help you to focus on data scientists and analysts, it provides access to thousands of pre-certified, job-ready candidates. This makes it much easier to find quality, proven candidates. Based on the job criteria you enter, our algorithm matches you with the best available candidates. 

3. Filter for the skills you need

Through our matching and filtering algorithms, you can directly reach out to the candidates that match your job requirements. These filtering tools focus on skills and experience which help you hire the best data scientist and data analyst candidates without bias, making for easier and fairer recruitment. 

4. Certified and ready to go 

On top of all of this, you get access to candidates certified by DataCamp. DataCamp learners have undergone rigorous testing before they’re certified, including technical assessments as well as tests of their ability to put together and present analysis. These assessments train them as a day to day data professionals, with hands-on experience in data storytelling as well as technical skills. 

So even if you’re new to the world of data, you can still hire the cream of the crop. Get started for free today. Let DataCamp Recruit take the guesswork out of hiring data-driven teams, and fill your open data roles faster.

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