6 ways to deal with the great data scientist shortage

Rather than wait for want ads to go unfilled, organizations should rethink, retrain, reorganize and reach out to fill the data science talent gap.

6 ways to deal with the great data scientist shortage
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The seemingly insatiable demand for data scientists continues to grow as organizations look for professionals who can glean insights from all the information they are gathering.

In a report released in January 2019, business and employment social media site LinkedIn listed data scientist as the most promising job in 2019, based on data about salaries, number of job openings, and year-over-year growth.

More than 4,000 data scientist job openings are expected for this year, according to the report, up 56 percent from 2018. Top skills within the category of data science include data mining, data analysis, and machine learning.

The problem is, companies often can’t fill these jobs fast enough because of the shortage of talent. That doesn’t mean they can’t acquire the types of skills data scientists typically possess, however. It might take some creative thinking and persistence, but organizations can deal with the great data scientist shortage in various ways. Here are some suggestions.

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