5 Key Data Science Job Market Trends
As a data scientist — or someone interested in the field — you know the industry is constantly evolving. If you want to remain competitive, you need to keep up with popular trends.
Data science is considered a relatively new career field.
The industry itself and its various platforms, tools and operations have been around for a few years now.
As a whole, it’s starting to pick up speed. Companies are bringing on more and more data-oriented personnel, and for good reason.
As a data scientist — or someone interested in the field — you know the industry is constantly evolving. If you want to remain competitive, you need to keep up with popular trends.
You also need to understand why data scientists are so prevalent and how the market will be shifting in the near future. And since we’re sitting right on the cusp of 2018, now is as good a time as any to look ahead.
What to Expect for Data Science in 2018
Whether you already have a foothold in the industry, or you’re looking to dive in, your mission should be the same: pay attention to current trends to ensure you’re both prepared and capable of handling what’s coming.
This is a huge one, especially with AI and machine learning growing in popularity. As a whole, automation means quite a few things, namely the steady and autonomous operation of a particular process or system.
A series of software tools and algorithms will be used to ingest, filter and highlight data that can be further analyzed.
You’d be forgiven for thinking automation would make data scientists obsolete. A lot of negative talk surrounds automation, particularly about uprooting jobs and careers. That’s not the case in data science, however.
Experts and experienced scientists will still be needed to highlight, identify and implement actionable insights. You can expect to see a lot of automation platforms crop up in the industry over the coming year.
Data empowerment is another important movement to keep your eye on. In some ways, “empowerment” sounds bold — even a little ominous. It’s just a buzzword though, used to explain a boost in data effectiveness for many parties.
To put it simply, the data and information that a company or organization is collecting doesn’t just belong hidden on a remote server somewhere, gathering dust. Furthermore, just because a chunk of data is not useful to the collector doesn’t mean it’s not useful to someone else.
Data empowerment is about the alignment or collaboration of everyone involved in a system. It means that everyone has access to the same tools and resources and the same data stores.
More importantly, it means putting data in the hands of the right people — those who can make use of it.
