Data scientists are essential for organizations looking to stay competitive and future-proof their business. With their ability to analyze and interpret complex data sets, they can provide valuable insights that help organizations make informed decisions and drive growth. It’s why data-driven organizations are 19 times more likely to be profitable, according to Mckinsey Global Institute.
Problem is, finding talented data scientists is tricky in today's climate. Join us as we delve into the reasons behind the shortage of proficient data scientists and uncover valuable recruitment strategies to help you assemble a winning team.
Everyone wants a data scientist these days, thanks to the rising importance of data-driven decision making in different industries. In fact, the U.S. Bureau of Labor Statistics projects almost 28% job growth for roles requiring data science skills by 2026, highlighting the surge in demand for skilled data scientists.
To make matters worse, the COVID-19 pandemic has disrupted industries worldwide, leading to an even greater need for data-driven solutions. Educational institutions have also found it challenging to keep up with the pace of change and train data talent to meet this growing demand, exacerbating the supply-demand gap for skilled data scientists. Plus the role itself:
is relatively new, and as a result, data scientists with a decade's worth of experience are rare;
is multidisciplinary — data scientists require a broad range of skills, including statistical analysis, programming and machine learning. This diverse skill set means that a significant skills gap exists;
is challenging, and candidates must demonstrate a history of achieving results. This experience leads to higher salaries: industry reports suggest that data scientists with 3-5 years of experience can earn an average salary of around $100,000, with pay rising alongside experience and skill.
Putting together your perfect data team can be a bit of a challenge when you consider the newness of the field, the wide range of skills needed, and the high salary expectations. To tackle this, you need to get creative and come up with some new strategies to find and recruit the right people — traditional search and recruitment tactics won’t cut it in this competitive landscape.
When hiring for your data team, it's better to go for people with a range of skills, instead of just those with super specialized expertise. For example, lots of companies are looking for candidates with degrees in computer science, engineering or math. Once you've got your team in place, you can always supplement them with MLaaS and analytics products like Azure or AWS.
You could also consider taking on psychology or business post-graduates. These subjects may not seem super tech-focused at first glance, but they can produce some top-notch statistical analysts with a deep understanding of systemic and global influences. So, why not give them a shot?
Additionally, if you want to build a high-performing team, it's all about putting together the right mix of people from the get-go. Once you've got your team, you can focus on helping them level up their skills. You can start everyone off with a similar foundation (and not break the bank on salaries), and then let them specialize based on their strengths and goals. This way, you can refine and grow your team as your goals and needs get more complex and ambitious.
Employers frequently overestimate the practical experience required when hiring to address skill gaps. The reality is, you likely don't need someone who's a master of every data science facet. So, consider asking targeted questions, such as whether you genuinely need statisticians who double as skilled coders or data visualizers who moonlight as analysts.
Rather than hunting for candidates who check every box, it's often more strategic to zero in on those with remarkable potential to grow into the role. This approach allows you to welcome individuals who seamlessly mesh with your team and contribute to achieving your long-term goals.
When it comes to data science, creativity is also key. As Tsvi Gal, CTO of Morgan Stanley, points out, you can't just rely on algorithms and follow them blindly. You need to be able to identify patterns in the data, even if they're not obvious at first. That's why Stanley often hires people with backgrounds in the arts – they have a different way of thinking that can be incredibly valuable in the data science world.
If you want to attract top talent in the competitive field of data science, you need to stand out from the pack as an employer. That means building a strong company culture that really speaks to the people you want to hire. A good starting point is to talk to your existing team and find out what they care about and where they see the business going.
Another important factor to consider is your employee benefits. What kind of perks can you offer that other companies don't? Maybe it's flexible working hours, generous vacation time, or opportunities for professional growth. By offering unique benefits, you can make your company more appealing to job seekers and keep your current team members happy too.
It’s always good to be aware of what people are saying about your business too. With so many windows into your brand – Facebook, LinkedIn, Twitter, Glassdoor, Indeed – candidates have plenty of ways to understand what you offer and how employees experience your company. How will top data scientists perceive your business when they hear what your current or old employees think? Understanding this can help you identify ways to improve before you hire or how to tackle certain conversations during the recruitment process.
When it comes to recruiting data scientists, you could spend forever scouring job boards or scrolling through LinkedIn profiles hoping to find the right fit. But why waste all that time and energy when you could tap into a specialized network of data professionals?
By partnering with a reputable recruitment agency like Data Logic, you can easily connect with a pool of vetted data experts, including scientists, engineers, and analysts. These are people who are already proven to have the skills, qualifications, and experience you're looking for in a candidate. And because they trust the agency to connect them with companies that share their values, you can be confident that they'll be a good fit for your organization.
The beauty of accessing a specialized network of data professionals is that it saves you valuable time without compromising on the quality of your candidates. No need to drive yourself crazy searching for the perfect data scientist when you can partner with an agency like Data Logic to do the heavy lifting for you.
Having the right mix of data scientists on your team is crucial for unlocking the insights and opportunities that will give your organization the competitive edge it needs to succeed. And when it comes to recruiting the best talent, why not leave it to the experts?
Let our team of data science specialists at Data Logic help you find the perfect candidates to drive your organization forward. With our extensive network and expertise in the field, we're equipped to connect you with the top-tier talent you need to thrive in today's data-driven landscape. So don't settle for a subpar team - let us help you assemble a winning lineup of data scientists to take your organization to the next level.
