Power BI vs Tableau vs QlikView
June 19th, 2019
The data science skills gap is nothing new. The data and analytics industry has always had a gap when finding the right people with technical skills, but the problem only seems to be growing for data scientists. Last year IBM predicted that “by 2020 the number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings to approximately 2,270,000”.
In the same report it was suggested that this gap isn’t just down to finding the right skills but also the money associated with it. As the skills and education – many job adverts require a masters or PhD from data science candidates (39%) – are in high demand the salaries can be huge. But the cost for the businesses don’t just stop there, there is cost behind the tools and technologies data scientists need to use, but there may also be additional training needed in order to do a particular role.
Fixing the data science and analytics skills gap won’t be easy but I believe it should start with graduates. While many universities are teaching computer science degrees they are not providing enough real business training in the key areas. The University of Stirling is aiming to beat this by providing extra courses for the students, teaching the students to use advanced analytics and how to apply them to real-life business scenarios. The Office of National Statistics is also getting behind this idea by ensuring the country and universities have the right resources in order to implement these data science courses.
Across America the popularity of coding and data science bootcamps is also increasing, and for some becoming an alternative to attending university. These data science bootcamps are very intensive training courses to make sure graduates have the right up-to-date skills that can easily transition into a business.
It also comes down to the recruitment process. As mentioned, many data science jobs require a masters or PhD but it has been suggested that people with these degrees can take 1 -2 years before they are actually ready to apply for the role and by that time the skills and technologies needed will have already rapidly shifted. And as the demand, and salaries, are high once they are in employment many data scientists aren’t inclined to move roles unless the salary and package offered is substantial.
If IBM’s research is proven true, the shortage of skilled data scientist is only going grow while the demand increases. This data science and analytics skills gap won’t close immediately but by training graduates and existing staff the gap can be closed slowly.
What do you think needs to be done to close the data skills gap? Has your business been affected by the skills gap?
This blog was originally published on LinkedIn. To read the original blog click here.