Three Ways To Stay Competitive While Solving The Data Scientist Skills Gap

Innovation Three Ways To Stay Competitive While Solving The Data Scientist Skills Gap Bill Pappas Forbes Councils Member Forbes Technology Council COUNCIL POST Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based) Sep 12, 2022, 09:45am EDT | Share to Facebook Share to Twitter Share to Linkedin Bill Pappas, Executive Vice President and Head of Global Technology and Operations, MetLife .

getty Tech companies, including those in the financial services sector, are still working on how to capitalize on an abundance of untapped data. In fact, incoming and stored data (when used responsibly and smartly) can provide benefits across customer experience, product development and business strategy. While data is also an important competitive advantage that can help enterprises surf rough waters and dynamically evaluate risk—particularly important considerations given today’s global market—one challenge remains: a lack of qualified data scientists.

It has been 10 years since Harvard Business Review named data scientist the “sexiest job of the 21st century,” and this sentiment still rings true in 2022. In fact, the Bureau of Labor Statistics reports that the expected growth rate in the data science field will be higher than the average of all other fields between now and 2029, and an article published by CIO notes that “recent research from industry analyst firm IDC showed that there are 210,000 data science jobs listed on LinkedIn. ” The data science skills gap isn’t new, however.

Now more than ever, employers need to figure out how to attract, retain and promote this key portion of their workforce. To do so, they need to invest in the right workplace culture. This isn’t a task just for the chief data officer, chief technology officer or technical heads but the full C-suite.

Here are three key considerations for employers looking to remain competitive in recruiting and retaining the best talent in the data science field. 1. Invest in a modern and diverse corporate culture.

A sustainable digital culture demands a modern workforce that embraces analytics, automation and strong data stewardship to leverage this new data landscape to the fullest. Moving from intuition-based to data-driven processes can build resiliency and an engaged workforce ready to tackle current and future market transitions. MORE FOR YOU Google Issues Warning For 2 Billion Chrome Users Forget The MacBook Pro, Apple Has Bigger Plans Google Discounts Pixel 6, Nest & Pixel Buds In Limited-Time Sale Event This philosophy must be enacted from the top down, with a C-suite committed to a data-driven corporate culture.

The commitment to culture should also include initiatives to hire and support a diverse team. In fact, while diverse viewpoints are vital to all teams and business areas, they’re core to structuring, transforming and testing data to ensure unbiased analytics. Companies have a lot of work to do in this area; we found that our chief data and analytics officer is one of only six women among Fortune 50 companies to hold that title.

Employers need to understand the importance and nuance of the work that data scientists are doing and ensure they have the necessary resources—including the right team and culture—to enact long-term payoffs when it comes to data management. By investing in a modern and diverse corporate culture, employers can ensure they’re meeting and exceeding the expectations of prospective talent today and into the future. 2.

Prioritize a nimble technology backbone. To truly see the ROI of data management and analysis, data teams need to be able to invest in or have access to systems that allow them to work smartly and efficiently. On the flip side, employers and senior leaders should find that having the right technology backbone in place means they can have more seamless access to the insights garnered from data.

A nimble technology backbone can enable the use of vast and complex data types as well as provide scalable computation to achieve these insights. Digital capabilities require a modern architecture to deliver a rich interactive customer experience. Again, this priority cannot rest with the CDO or CTO alone but should be built into every part of a business.

3. Provide upskilling opportunities. With such a limited pool of trained data scientists, employers should also provide their existing employee base with opportunities to develop their own data analytics skills—a skill set many are seeking to hone.

All professionals can benefit from skills such as data storytelling and visualization to test their intuitions. Upskilling technical talent on topics like artificial intelligence and robotic process automation can rapidly identify hidden insights and trends and put them into the hands of decision-makers. As the momentum behind AI, automation, and data and analytics in business and society continues to accelerate, C-suite leaders must work to ensure they are investing in a diverse and modern workplace culture, prioritizing a nimble technology backbone and upskilling technical talent by providing employees with opportunities to learn and grow their skill sets.

Filling the gap in data science is not solvable by one individual or executive; it requires involvement and leadership across all functions and divisions. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? Follow me on LinkedIn .

Check out my website . Bill Pappas Editorial Standards Print Reprints & Permissions.