Machine learning engineers and data scientists topped LinkedIn’s 2017 U.S. Emerging Jobs Report, thanks to high rates of job growth over the last five years. That growth was spurred, in part, by the increasing importance of data capabilities to both tech and non-tech companies that wish to stay ahead in their industries.

While the LinkedIn study used job ads to reveal employers’ demand, another study compared 1,000 data scientist LinkedIn profiles to gain a better understanding of the typical data scientist’s skills. The study revealed that the typical data scientist is a male who speaks one foreign language, has four and a half years of overall work experience (median), works with R and/or Python, and holds a Master’s and/or PhD degree.

These findings give insight into how one can prepare to become a data scientist and which industries are hiring, including tech/IT companies, industrial firms, and the financial sector. Similarly, the LinkedIn report is encouraging for aspiring data scientists: Despite 650 percent growth in data science roles since 2012, only 35,000 people in the U.S. currently have data science skills.

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Image Source: LinkedIn 

The high demand and limited supply of data scientists and engineers will pose some challenges for companies across industries in the coming years. Just hiring a data scientist or engineer is not enough; managers will need to take special care to align business and data teams and enable data scientists to become self-sufficientOtherwise, they might not get their expected ROI in data science, a problem 78% of companies are encountering.

As the job market shifts towards more technical roles, companies need to ensure that their data scientists have the tools they need to succeed in their jobs. A data science platform that makes data science collaborative, scalable, and impactful is essential to bring together data science, business, and IT teams.

The shift in the job market has more implications than just employment. Many experts have shared their thoughts on how the increasing demand for data science capabilities and  machine learning will impact the future. Data scientists and business leaders can find more resources to navigate the changing landscape  here.

Savannah Burchfiel
Author
Savannah Burchfiel

Content Specialist at DataScience.com.