Long before the novel coronavirus caused a tech hiring slowdown, jobs calling for machine learning or AI skills were a hot trend. The pandemic has done nothing to change that.
If anything, COVID-19 is likely to increase the demand for AI professionals, says IDC analyst Ritu Jyoti.
“Because of the pandemic, IDC believes that AI spending and employment will increase among healthcare providers, education, insurance, pharmaceutical companies and federal governments,” she said, estimating the increase could be as high as 16%.
CIO.com did a survey to see what the emerging AI jobs are likely to be. Among the nine the magazine turned up were some familiar titles – data scientist, for example — and at least one that isn’t a job title but a description of skills. Familiar or emerging, all of the jobs have this in common: They not only require AI skills, but also a good grasp of business essentials.
Chief data scientist, a job that already exists at many companies in and out of the tech sector, is one of those familiar titles that is evolving from statistician to more of a business technologist. Increasingly, the job will require a basic understanding of the underlying technology as well as an appreciation of business needs.
“Data scientists know what data to use and what algorithms to deploy to get the best results, working with data engineers and software developers to turn this know-how into working applications — and with business units to ensure the technology meets business needs,” says CIO.com.
Data alone may yield interesting intelligence, but to wrest actionable value companies have long employed analysts. Emerging now is a category of analyst who works directly with data scientists and engineers and with the business side. These analysts not only must have an intimate knowledge of the operation, CIO.com says they also must be able to speak the AI technical language.
If this job sounds similar to the emerging chief data scientist role, it is — to a degree. These analysts will serve more as translators. They may not need to be fluent in data science, but they will need a higher level of technical expertise and a high degree of business acumen.
Finding and hiring professionals with these skills will not be easy. Anand Rao, partner and global AI leader at PricewaterhouseCoopers, told CIO.com that because schools are training for entry-level technical jobs, “The business and executive jobs need to be grown and cultivated within the firm and will pose a significant challenge to fill.”
One job with a familiar title that will be radically different on an AI team is quality assurance manager. Unlike traditional QA roles, an AI quality assurance specialist will be less concerned with the quality of the code than the quality of the data.
In an AI setting, quality assurance will be concerned with “incomplete, out of date, or biased training data sets,” says CIO.com. Though companies have yet to advertise AI quality assurance jobs, that’s coming. “Biased data is a particularly thorny problem that can lead not only to bad results, but also regulatory implications, bad publicity, fines, or lawsuits.”
Finally, notes the CIO article, are the emerging “citizen data scientists.” More a job description than a job title, these professionals will be skilled in using off-the-shelf tools to perform AI-related data tasks. As these AI analytics tools become increasingly easier to use, workers reskilled for AI and machine learning will take over from the highly trained – and expensive – data scientists who now do the job.
Photo by Michael Dziedzic on Unsplash
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