The Growth in Demand for Data Scientists in 2019

A recent LinkedIn United States Workforce Report for January 2019 outlined a continued shortage of data scientists and data engineers across the United States. A similar trend in data talent shortage could be seen in IBM findings, which projected that by 2020 the total number of jobs for all data professionals in the United States would increase by 364,000 openings to 2,720,000.

Previously, LinkedIn found that demand for data scientists in the United States was “off the charts.” The study concluded that, in August 2018, companies were looking for 151,717 more data scientists than the United States job market could offer. This number was derived by comparing the skills of more than 150 million LinkedIn members with a weighted mix of skills that appear in job postings and the relative frequency at which professionals with a certain skill set are hired relative to professionals without that skill set. According to the study, the largest shortage of data science professionals was in New York City, San Francisco Bay Area, and Los Angeles. In general, data tech skills such as data storage, data science, and data engineering had become more in demand in the largest United States cities over the previous three years, from 2015 to 2018.

A recent survey by O’Reilly indicated that market demand for data scientists and data engineers was strong not only in the United States but globally. This trend was also reflected in reports from the World Economic Forum and IBM, which put yearly demand for data science and data engineering roles at nearly 700,000 openings by 2020. This skills shortage affects companies that employ a data-driven approach and can limit their ability to make strong strategic decisions at scale.

Data skills were increasingly in demand as more companies tried to become truly data-driven organizations. Below is a quick overview of the top data skills for 2019:

• Artificial intelligence. To drive innovation within large companies and help new startups disrupt industries and produce machines with increasingly capable automated behavior.
• Machine learning. As a subset of artificial intelligence, it allows companies to build models that analyze complex data sets while delivering quicker and more accurate results.
• Data visualization. It has become the de facto standard for modern business intelligence. Data visualization tools continue to play an important role in democratizing analytics and making data-driven insights transparent to employees.
• Language processing skills. These are in strong demand with the rise of digital assistants and the trend toward automated customer service.
• Data storage, optimization, and modeling. This has a direct impact on the quality of data science projects. Where data is, how to collect and process it, and where it is best stored are all questions that need answers to support production analytics systems.
• Quantitative and predictive analysis. These remain important skills for any data professional.

At the same time, job-search firm Indeed reported that while more job seekers were becoming interested in data science jobs, the number of employer postings was rising even faster than the number of interested applicants.

“The bargaining power in data science remains with the job seekers.”

Andrew Flowers, Indeed economist

Data scientist salaries by location#

The table below shows average salaries, both raw and adjusted, for the most active regions, along with the reported change in raw salaries since the previous year.

Location	Average salary (cost-of-living adjusted), 2018	Average salary (raw), 2018	% change since 2017
Houston-Woodlands-Sugarland, Texas	$123,010	$137,648	16.5%
San Francisco-Oakland-Hayward, California	$121,193	$166,519	13.7%
Seattle-Tacoma-Bellevue, Washington	$119,141	$146,088	13.7%
Atlanta-Sandy Springs-Roswell, Georgia	$110,171	$117,002	12.7%
San Jose-Sunnyvale-Santa Clara, California	$109,668	$153,535	3.8%
Bridgeport-Stamford-Norwalk, Connecticut	$109,179	$144,444	NA
New York-Newark-Jersey City, New York / New Jersey	$108,681	$146,067	7.5%
Boston-Cambridge-Newton, Massachusetts / New Hampshire	$108,596	$132,922	6.3%
Austin-Round Rock, Texas	$108,410	$119,359	5.8%
Chicago-Naperville-Elgin, Illinois / Indiana / Wisconsin	$108,141	$123,713	15.8%
Los Angeles-Long Beach-Anaheim, California	$105,355	$136,645	3.0%
Philadelphia-Camden-Wilmington, Pennsylvania / New Jersey / Delaware / Maryland	$104,991	$122,524	3.6%
Dallas-Fort Worth-Arlington, Texas	$104,947	$115,862	17.2%
St. Louis, Missouri	$103,694	$103,798	3.8%
San Diego-Carlsbad, California	$99,852	$127,910	NA
Washington-Arlington-Alexandria, D.C. / Virginia / Maryland / West Virginia	$99,255	$130,222	-5.6%
Des Moines-West Des Moines, Iowa	$98,021	$102,138	NA
Baltimore-Columbia-Towson, Maryland	$95,751	$113,178	NA
Tampa-St. Petersburg-Clearwater, Florida	$86,543	$95,111	NA

Source: Indeed.com

Resources#

1. LinkedIn Workforce Report, United States, January 2019
2. LinkedIn Workforce Report, United States, August 2018
3. IBM, “The Quant Crunch: How the Demand for Data Science Skills Is Disrupting the Job Market”
4. O’Reilly, “How Companies Are Putting AI to Work Through Deep Learning”
5. Indeed, “Data Scientist: A Hot Job That Pays Well”