Scott Alan Ritchie/Shutterstock
Once the industrial base of the US, the Midwest has struggled in the high-tech era to capture the talent-driven growth enjoyed by coastal cities like Boston and San Francisco, but the region’s fortunes are changing fast. In the past year or so, a burgeoning Midwestern tech scene has begun attracting more attention from venture capitalists and Silicon Valley giants, with many local startups and big-company expansions focusing on the middle-skill roles for which the tech sector’s demand is insatiable, but that are still in short supply nationwide. These “mid-tech” or “new-collar” jobs are described as a 21st century analog to the factory jobs of the past—and as such, a promising path to revival for the industrial Midwest.
High-tech industries including major international firms have been making some big bets in the region: The Indian IT services and business process outsourcing giant Infosys is planning a sprawling campus near Indianapolis, which aims to create 3,000 new jobs within five years, while the Taiwanese multinational Foxconn Technology Group made a deal with the Wisconsin state government last year to build a display panel factory there, which will see the company invest as much as $10 billion and hire as many as 13,000 people. Several midwestern cities are on the list of finalists in the competition to host Amazon’s second headquarters, though Detroit, for example, didn’t make the cut, partly due to a lack of readily available talent.
Yet “mid-tech” companies and regional outposts of tech giants are just one side of the Midwest’s high-tech renaissance. Over the weekend, VentureBeat reporter Anna Hensel took a look at the growing community of AI and machine learning startups in the heartland:
“The real benefit of artificial intelligence is the application to traditional problems and products that the world needs, and the really successful companies have that domain knowledge that they can understand how to apply this technology,” [Chris Olsen, a partner at Columbus, Ohio VC firm Drive Capital,] told VentureBeat in a phone interview. “We see more of those domain experts in these industries [with] massive chunks of GDP that exist here in the Midwest.”
At a time when their skills are needed in organizations of all shapes, sizes, and industries, data scientists are in short supply, representing one of the most significant skills gaps in today’s labor market. But what if recruiters are coming up short not because there aren’t enough qualified candidates, but rather because their definition of “qualified” is too constrained? Vin Vashishta, founder and chief data scientist at V-Squared Data Strategy Consulting, makes the case at Fast Company that employers are chasing unrealistic qualifications for their data talent:
I honestly feel for recruiters who are tasked with filing data-science and machine-learning job openings. The list of requirements that employers draw up for those roles is pure bravado with a side of madness: “10 years of data science with at least five years in natural-language processing and either a Master’s or PhD” (never mind that I can count on one hand the number of data scientists who were building for production back in 2007). Others ask for experience with three different programming languages, 10 platforms, a niche algorithm set, leadership skills—and by this point I’m typically only halfway through reading the job qualifications.
Ask any tech recruiter and they’ll tell you about the stack of job openings like these that they’ve been unable to fill for the past six months to a year. Every couple of weeks, the client calls and berates them for not being able to send them quality candidates. After awhile everyone involved throws up their hands and calls it a “skills gap.” It isn’t.
Google doesn’t require a PhD to be a machine-learning engineer. A recent survey found that only one in four data scientists has a PhD. Yet I still see advanced-degree requirements on the vast majority of data-science and machine-learning job descriptions. Most companies just throw it in unthinkingly. But unless they’re investing heavily in advanced research, it’s pointless.
Over-reliance on educational qualifications and experience for emerging roles is a something employers will have to get over if they want to fill talent shortages in data science and other valuable technical roles. Many organizations seek out computer science majors to fill these roles, but many talented computer programmers and software developers didn’t study computer science in college, or don’t have traditional college educations at all.
Krista Kennell / Shutterstock.com
In an op-ed at USA Today, IBM CEO Ginni Rometty discusses her organization’s plans to hire 25,000 employees in the US and invest $1 billion in training and development over the next four years, to help meet the demand for new skills created by new technologies. “The surprising thing,” she adds, “is that not all these positions require advanced education”:
This is not about white collar vs. blue collar jobs, but about the “new collar” jobs that employers in many industries demand, but which remain largely unfilled. … In fact, at a number of IBM’s locations spread across the United States, as many as one-third of employees don’t have a four-year degree. What matters most is that these employees – with jobs such as cloud computing technicians and services delivery specialists – have relevant skills, often obtained through vocational training.
Indeed, skills matter for all of these new positions, even if they are not always acquired in traditional ways. That is why IBM designed a new educational model that many other companies have embraced – six-year public high schools combining a relevant traditional curriculum with necessary skills from community colleges, mentoring and real-world job experience. The first of these schools – called Pathways in Technology Early College High School, or P-TECH – opened five years ago in Brooklyn. It has achieved graduation rates and successful job placement that rival elite private schools, with 35% of students from the first class graduating one to two years ahead of schedule with both high school diplomas and two-year college degrees.
This strikes me as a big deal. The “new collar” neologism will stick and is a fascinating example of HR as PR. Rometty’s ideas strike at a core challenge in the US economy today—namely the shortage of skilled workers to fill available jobs—but what I’m curious about is what kind of career paths lie ahead for these “new collar” workers.