Top 10 rising and falling buzzwords in tech jobs

Among the top five buzzwords, only two were known a year ago.

Technology changes frequently, and so do its buzzwords.

Some of the most effective terms a year ago, such as big data, no longer have the same cachet with job applicants, according to a study of more than 500,000 tech job postings by Seattle startup Textio. Stale jargon is being replaced by hotter trends, including artificial intelligence and real-time data.

For the study, Textio tracked more than 50,000 unique phrases commonly seen in tech job listings, said Kieran Snyder, the company's chief executive officer. The startup compiled a list of terms that experienced the biggest changes in impact, positively and negatively, over the last year.

Among the five biggest losers, none were turn-offs to job candidates in 2014, which shows how fast the industry changes. Among the top five buzzwords, only two were even on the map a year ago, Snyder said.

Textio creates language-analysis software used by more than 3,000 companies, including Twitter and Expedia, to edit their job postings. The tools rely on artificial intelligence (good buzzword!) to scan text and suggest tweaks designed to improve a company's chances of attracting strong applicants. Textio also offers tips for bringing in more diverse candidates. For example, female professionals aren't usually interested in office Nerf battles or being classified as "code ninjas."

The startup's backers include Cowboy Ventures and Upside Partnership. Bloomberg Beta, the venture capital arm of Bloomberg LP, is also an investor in Textio.

Textio's tool can't predict whether a new hire will ultimately be successful or prove a good cultural fit in a job. Nor can it ensure that employees will remain happy and effective after they start working. Snyder said her startup is developing software to improve retention and minimize attrition, such as performance-review and feedback tools that verify whether a company's processes are effective, constructive, and free of bias.

In the meantime, global companies in various industries are willing to give the recruitment software a try to see if it can improve a process that's often seen as an afterthought. (Snyder said she advises companies against the common practice of pasting parts of old job listings into new ones.) It may be especially enticing to companies looking for an edge in Silicon Valley's competitive hiring environment.

Each term included in the study was measured using three main criteria: the number of people applying for a job containing the phrase, the percentage of those applicants with the skills and background to qualify, and the time it took to fill the role since the job was posted. The results were then ranked by changes in effectiveness from a year ago.

Here are the top five winners and losers.

Rising:

• Artificial intelligence: Elon Musk and Stephen Hawking may think it's scary, but tech job applicants are running toward listings that mention AI. Over the past six months, the term's usage among the best-performing tech job listings has quintupled.

• Real-time data: Big data bad. Real- time data good. Supposedly, this term, unlike its predecessor, conveys that the hiring company wants to build products based on the latest information, rather than just a lot of information.

• High availability: This places an importance on building software that is always accessible and almost never goes down, which is a technical challenge many engineers appreciate. It's showing up in 42 percent more job listings than a year ago.

• Robust and scalable: Usage of the two words together started to blow up over the summer and has tripled over the past two months. The jargon generally refers to software that's powerful, yet able to serve lots of users.

• Inclusive: Thanks to the rising importance of diverse workplaces to many applicants, particularly in the tech industry, job postings benefit from a reference to inclusiveness. The words "diverse" and "diversity" have long been a popular choice to fill out corporate boilerplate, but the terms may be losing their meaning. Perhaps that's why "inclusive" has surged in popularity over the past six months.

Falling:

• Big data: This is the biggest loser in technology job ads, according to Textio, a big data company that will no longer call itself that. Two years ago, everything was about big data, but Snyder noticed that it had started to drop off five or six months ago. Today, engineering jobs that mention "big data" perform 30 percent worse, on average, than those that do not, she said. "Now it's so saturated that you'd better talk about AI and not big data."

• Virtual team or V-team: Corporate jargon turns off many applicants, and this term, which refers to telecommuting, is more than 10 times as likely to appear in jobs with low applicant counts than in successful listings.

• Troubleshooting: This is a key skill for many tech workers, but recruiters would be better off calling it "problem solving," "fixing," or "diagnosing," said Snyder. Troubleshooting performs twice as bad as those other terms.

• Subject matter expert: You might think being an expert is a good thing, but the term carries a connotation that the ideal candidate knows one thing very well and little about anything else, Snyder said. She said tech applicants want to be "full- stack engineers," a buzzword that performs 32 percent better than "subject matter expert."

• Drug-free workplace: A guaranteed way to sink your listing is using this phrase. It makes any tech job advertisement more than 20 times likelier to perform in the lowest quartile. And it's getting worse.

Six months ago, the impact was only half as bad. Why?

Snyder doesn't know for sure, but she suspects applicants may read it as code for a buttoned- down workplace. That would turn off people looking for casual work environments, flexible hours, and lax dress codes. "Perhaps companies that feel compelled to advertise their 'drug-free workplaces' have environments that are more rule-governed to begin with," Snyder said. "It's language that often appears in government jobs or very traditional large enterprises with core businesses outside of tech. Those are not environments that are traditionally known for their laissez-faire attitudes."