Predictions: 2019 Data Science Jobs Market

The data science and analytics job market is growing rapidly. What's more, after a year of wages staying comparatively flat, data science and analytics experts can look forward to rises in 2019. That's according to a series of 2019 predictions from quantitative recruitment specialist firm BurtchWorks' managing director, Linda Burtch.

If your organization plans to recruit these professionals in 2019, or if you are a data scientist looking to make some career moves this year, these predictions offer some useful insight about what you can assume in the year ahead. What's driving some of the changes? How can you leverage these opportunities?

There are several forces in play right now, Burtch told InformationWeek in an interview. Organizations across almost all industries have recognized that analytics can make them more intelligent and more profitable. Career-focused young people are taking degrees to prepare themselves for such jobs. That has extended the talent pool for businesses looking to hire, but demand for these employees is still outperforming supply.

One of the most significant factors influencing the data science job market in 2019 will probably be a constant freeze on quality processing for H1-B visas and other visa programs, as per Burtch. The change has meant, in 2018, delays of 4 to 6 months before job applicants could start at a new position.

"Since there is some dispute over if and how the US visa process should be overhauled, I am skeptical that this situation will be cleaned up in 2019," Burtch wrote in a blog post about her predictions. "One tactic that I've seen some firms use to circumvent the US visa tangle is to set up their visa-requiring candidates in Canada instead."

In addition to Canada, other places in North America may be undergoing some job creation as businesses in the key data science hubs like the San Francisco Bay Area and the New York City area look to build new offices in less costly markets. Burtch said that these enterprises are opening offices in urban areas like Chicago, Austin, and Detroit, to attract and contend for quantitative talent that may not want to pay the high housing costs in those other markets. Though you may not have to move to San Francisco to work in one of the top jobs, businesses are still reluctant to hire remote employees, Burtch said.

Yet the competition may be getting tough in major cities. Burtch told InformationWeek that some employers in Washington DC and New York have stated concern about Amazon locating its new headquarters processes in those two cities. The web services and online retail giant will surge the already tough competition for talent in those cities.

To continue to draw top talent in data science and analytics, enterprises may want to consider the tools obtainable to their employees. Burtch points out that in last year's survey, Python displayed a lot of momentum and in 2019 she assumes it to outpace R and SAS as the preferred tool among quantitative specialists.

In terms of pursuing educational opportunities, Burtch has two predictions. First, she considers that the "upskilling" trend will last, and employers are getting more thoughtful about internal training. Enterprises may turn to bootcamps to help "quant-adjacent" employees gain analytics skills. 

Or maybe your current analytics pros can obtain some knowledge with additional AI skills like natural language processing or deep learning.

Second, if you are considering an MBA to boost your career, you may want to reassess. Burtch predicts that the MS in analytics degree will outdo the traditional MBA.

"In 2018, 70% of two-year MBA programs reported a drop in applications. Meanwhile, new online data science programs continue to pop up to address the clear demand for quantitative talent," Burtch wrote in her blog post.