5. Python is the new R
Last year’s SAS, R, or Python survey results showed that Python is gaining in popularity among both data scientists and traditional analytics professionals. As a stable and scalable option with tons of functionality, Python is quickly becoming the tool of choice over R. And, as an open source tool, Python’s versatility is continuing to develop at the field matures.
6. Employers favoring other tools will hesitate to hire SAS-only professionals
Once the gold standard in analytics tools, SAS is now more a marker of an outdated skillset. Analytics professionals who are only proficient in SAS will find themselves limited to companies who are still lagging behind the open source movement. Knowing only one language is quickly falling out of fashion, so make sure you update your skills before you get left behind! In a field that changes so fast, you should never get too comfortable. Python may be the hot tool today, but it could be something else tomorrow.
7. Staying hands-on is more important than ever
While we’ve always recommended continuous learning as a way to stay current, it’s become clear that staying hands-on with data projects is key, even for top-level management positions. This is especially common in tech or younger firms, which have a much flatter organizational structure than traditional companies. In a market where your skills can become obsolete in just a few years, staying close to the data is the best way to make sure you keep your skills fresh and marketable.
8. China is the Wild West of analytics
China is accelerating quickly as a quantitative powerhouse, with not only investments in US companies, but also a booming local tech scene with companies like Baidu, Alibaba, and Tencent. With access to troves of data and a developing economy, be on the lookout for Chinese firms snatching up talent from the US.
9. Traditional organizations are spawning quantitative startups
Over the past few years we’ve noticed more traditional companies have been spawning new ventures to develop a new idea or product outside of the larger organization, and many of them have data in their DNA. These faster, more agile startups include companies like Arity, which was created by Allstate, and Gamut, created by Grainger. These groups have the advantage of being backed a large corporation, while still being able to think and react quickly. Creating some distance between the parent company and the startup entity can also help with recruiting young talent that might hesitate to join a traditional name-brand organization.
10. The acquihire is big in data Science
With the continued lack of talent, companies looking to hire large numbers of data scientists are having to get creative about where they find quantitative experts. Popular among Silicon Valley tech giants like Google and Facebook over the past few years, the acquihire is starting to see some popularity outside the Valley as well, as I’m seeing companies snapping up data science consulting firms in a bid to absorb their talent.
What won’t happen:
1. data scientists will not become obsolete through automation
While I think it’s fair to expect that many “data janitorial” tasks will be automated in the future, I believe this will free up data scientists for more higher-level tasks, as opposed to automating them out of existence. Automation may shift job responsibilities for data scientists, but analytical thinking and the ability to communicate strategic insights from data won’t go out of style any time soon. And, we are not yet close to filling all the job openings for quantitative professionals.
What do you think of this year’s predictions? Do you see any new tools on the horizon, or do you believe data science popularity is due for a reckoning of sorts? Let me know in the comments!
Want to hear more about these predictions? Check out our webinar recording on YouTube, or watch the video below, to hear more about how these predictions will shake affect both employers and quantitative professionals – and make sure you’re prepared for 2018!
Original. Reposted with permission.
- Four Big data Trends for 2018
- Back to the Future: 2018 Big data and data Science Prognostications
- Data Scientist – best job in America, 3 years in a row