According to a new report form the Business-Higher Education Forum, there is a massive shortage of data scientists to meet the growing demand for analytics in both higher education and corporate America. The study estimates that 2.72 million new job postings in 2020 will target people with analytics and data science skills.
So, who exactly are these data scientists who are in such high demand? A data scientist is someone who, with the help of technology, can see how certain data might be more valuable than other data, and then draw accurate conclusions from that data.
Today’s data scientists evolved from the statisticians and data analysts of 10 to 12 years ago. They were great numbers people who could be trained to determine how the numbers could be used to solve business problems. Now, data scientists must be able to work with increasingly complex data sets and software, understand statistics and machine learning, and explain their findings in a business context. Increasingly sophisticated technology tools help human data scientists deal with the sheer volume of data that’s produced each day.
However, becoming a data scientist is about more than learning how to use specialized tools. There’s also the science part, which requires you to determine what the question should be instead of answering an existing question. It requires you to gather and organize the right data and determine how it should be analyzed rather than simply entering a query into an analytics platform. It requires you to create your own models, predictions and decision-making systems to deliver valuable insights that move business forward. Long story short, data science is a competitive advantage that requires a true data scientist to develop.
Unfortunately, there’s a significant gap between what organizations need and what higher education is delivering. A Gallup poll found that 69 percent of employers say candidates with data science skills are more likely to land jobs, but only 23 percent of college leaders said their graduates will have those skills. This “fundamental disconnect” between employers and higher education threatens our country’s economic competitiveness.
A big reason for the skills gap is “an educational culture where both faculty and students devote little time outside of their own specialties,” according to the Business-Higher Education Forum report. For example, students who are data science majors are prepared for real-world jobs, but business majors who could also benefit from a data science background are not.
Colleges and universities have begun to respond to the shortage of data scientists with more programs in data science and analytics. More schools are making these programs available to all undergraduates so students can learn how to apply data science techniques to specific areas of study. Schools are also encouraging participation from students with diverse socioeconomic backgrounds who might bring different perspectives to data science beyond business context. Instead of focusing solely on how to profit from data science, how can data science be used to benefit the greater good?
Higher education continues to lag behind the demand for qualified data scientists, but progress is being made. While employers need to do their part to address the skills gap by adapting their hiring practices, colleges and universities must continue to develop specialized data science and analytics programs and promote them to a wider range of students.