Data Jobs Enjoy Strong Demand in December

As we close out 2019, it’s clear that data is king, at least when it comes to the jobs that employers demand. Our December breakdown of data from Burning Glass’s NOVA platform (which analyzes millions of active job postings) doesn’t offer many surprises from previous months, but makes it clear that companies really, really want mathematicians, statisticians, and data engineers and scientists to join their ranks.

Over the past several months, there’s been little change in these rankings, which are based on year-over-year job growth. “Mathematician” tops the list of jobs (yet again) followed by data engineer; and those two jobs have experienced far greater year-over-year growth in postings than every other position in the top ranks.

What lessons can we draw from these rankings? If you want to add some skills that will boost your career, focusing on anything data-related certainly can’t hurt; it seems likely that companies will want to fill the jobs listed above for quite some time to come. 

In addition to skills, some workers attempt to boost their marketability by pursuing certifications. For example, a data analyst interested in increasing their marketability (as well as their salary) might target certifications such as CCA Data AnalystSAS Certified Data Scientist, or the Data Science Council of America Certification. In cybersecurity, certifications (and a solid working knowledge of data tools) are likewise key.

It’s also important to keep in mind that your career is a marathon, not a sprint, and that it takes time to develop the skills you’ll need to climb the ladder. The good news is, there’s no one pre-defined route to the C-suite or director level; as you can see from the following visualization tracing out a data scientist’s career, there are many ways to progress:

As we move into the New Year, keep your skills up-to-date, and stay flexible—you never know when your next big opportunity is going to come. It’s clear that employers are still on the lookout for all kinds of talent… especially talent that’s really good at wrangling datasets.