Tech Hiring Trends: Buzzwords, Trump Effect, and Gender-Pay Gap

As the tech economy continues its historic boom, here’s three views of labor market trends released this week, including the rise and fall of buzzwords in engineering job postings; the Trump Administration’s impact on U.S. companies’ interest in foreign workers; and another disappointing look at the gender-pay gap.

—In the last two years, big data has fallen off the buzzword bingo card. Data is table-stakes for doing practically anything interesting in tech, and it’s the fuel for machine learning algorithms. And of course we’re not talking about a little data here or there. It’s got to be big. So there’s probably not much need to signal that in an engineering job post anymore, and indeed, that’s what a new analysis by augmented writing company Textio shows. The term’s usage peaked in 2015 and has since declined to 2012 levels.

Meanwhile, anyone even vaguely following tech knows that the terms machine learning and artificial intelligence—regardless of their meaning or lack thereof—have spiked in the last two years. One piece of evidence: A Bloomberg analysis from earlier this year found that “artificial intelligence” was mentioned in 191 company earnings call transcripts published on the Bloomberg Transcript wire in the fourth quarter of 2016, up from 44 for the same period in 2015, and just 17 in the fourth quarter of 2014.

Another: Microsoft (NASDAQ: MSFT) updated its corporate mission statement in its just-issued 2017 annual report to read: “Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”).” The mission statement in the 2016 report described the same strategy, but “for a mobile-first, cloud-first world,” and included only one mention of artificial intelligence, in CEO Satya Nadella’s shareholder letter, where A.I. remained in the realm of research: “Within our research labs we’re hard at work on advanced machine learning—artificial intelligence—that will produce forewarnings that can put an end to distracted driving and one day identify a crisis like Zika before it happens.”

That’s not surprising, given Microsoft’s reorganization around A.I. in fall of 2016, about which it offered more detail earlier this summer.

Textio’s analysis of millions of job listings from the last two years finds that in 2015, 13.3 percent of new software engineering job posts contained one or more of the phrases artificial intelligence, AI, machine learning, ML, and machine intelligence. “Today, usage of these phrases in engineering jobs is up to nearly 20 percent—and still increasing,” writes co-founder and CEO Kieran Snyder in a blog post outlining the findings.

However, the effectiveness of job postings using those buzzwords has diminished as they have become more common. Textio measures this by looking at how quickly jobs described with these phrases are filled.

Textio identified a handful of phrases appearing more frequently in job posts in the last year: deep learning, neural net, chatbot, Internet of Things, and PaaS (platform as a service). They represent more specific descriptions of technologies that fit under the headings of AI and ML, perhaps a way for employers to signal that they’re serious about this, not just slapping on another buzzword to attract talent. Of course, these, too, will inevitably be replaced in a few months or years by the next batch.

—The election of Donald Trump coincided with a marked downturn in interest in foreign workers on the part of U.S. companies, according to an analysis from job-matching technology company Hired. Looking at more than 175,000 interview requests and job offers made on its marketplace in the last year, Hired found a 37 percent decrease in requests from U.S. employers to foreign workers from the second quarter of 2016 to the second quarter of 2017. (The decrease was even more pronounced in the immediate aftermath of the election, with requests down 60 percent in the fourth quarter of 2016.)

Hired also surveyed 362 tech workers—270 U.S. citizens, and 92 non-citizens—using its job-finding platform on topics including their appetite for jobs in the U.S.; their views of the H-1B visa program—a target of the Trump Administration’s immigration reforms; and their overall view of the administration’s impact on the tech industry.

“Sixty percent of our survey respondents indicated that they believe the current administration will have a negative impact on the tech industry, and almost a quarter say they are less likely to start a company in the U.S. as a result,” Hired says in a blog post announcing its findings. “Combined with recently announced plans to eliminate a federal rule that lets foreign entrepreneurs come to the U.S. for the purposes of starting new companies, it all adds up to a troubling outlook for the U.S.’s ability to retain talent and foster innovation.”

Hired performed a similar analysis in the wake of the U.K.’s decision last year to leave the European Union.

“In both countries, the need for tech talent remains at an all-time high, and if companies can’t rely on foreign workers to help cover shortfalls in domestic supply, we’re likely to see an exacerbation of the skills gap. In fact, we’re already seeing early signs pointing to this trend, as the number of interview requests per user on the Hired platform has steadily increased in recent months,” the San Francisco company says.

—Highly educated Seattle women—those with graduate or professional degrees—earn only 68 cents for each dollar a man with a similar education is paid. That’s a bigger gap than would be expected in a notoriously liberal city, according to an insightful look at the gender-pay gap in the 50 largest U.S. cities by Seattle-based LiveStories.

“Baltimore, Boston, Denver, and Nashville—four cities with populations roughly the same as Seattle—do not exhibit this pattern,” LiveStories finds. “Women with graduate degrees in these cities have median incomes much nearer to parity with men than they do in Seattle.”

The startup, which makes a platform for analyzing and visualizing government data, crunched median income data for people over 25 from 2011 to 2015 from the American Community Survey, an annual data-gathering effort of the U.S. Census Bureau conducted between the actual census, which is taken each decade. LiveStories says its methodology “yields a larger national gap (72 cents on the dollar) than some other reported figures, which often include younger workers or use aggregate incomes.”

Read the full analysis here.

Benjamin Romano is editor of Xconomy Seattle. Email him at bromano [at] xconomy.com. Follow @bromano

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