Artificial intelligence has been dominating headlines for years, with doomsday cries about robots stealing jobs and Jetsons-esque predictions about space travel. But underneath all of that hype, machine learning has made huge advancements, and companies are hungry to reap the benefits, whether it be to power a new cybersecurity tool, create customized shopping experiences, or power better search capabilities.
Of course, the first step for any company that wants to actually build or implement machine learning applications is finding the right talent. Data shows that machine learning is one of the most sought-after skills in tech. Combine that with the short supply of qualified candidates, and it’s easy to understand why salaries in data science and other fields are steadily increasing. Yet, many companies are still struggling to wrap their head around how they can find the right candidate for the job.
Hiring machine learning talent is challenging for several reasons. Not only is there a short supply of talent, but it’s also challenging for hiring managers to identify the correct candidate for the role. Because the many of the required skills aren’t something that can be learned from a textbook, candidates will not only need to apply the algorithms they’re familiar with, they will need to rely on their experience with data to come up with a valid solution to any given problem. This is also a brand new territory for most hiring managers, so they have no idea what skill set they should be looking for, what specific questions to ask throughout the interview process, or how to evaluate candidates’ hard skills.
So if you’re in a position to hire, what should you be looking for? When it comes to making key hires on your data science or machine learning teams, there are a number of things you can do to find the right candidate:
According to McKinsey’s State of Machine Learning and AI, the estimated total annual external investment in AI was between $8B to $12B in 2016, with machine learning attracting nearly 60% of that investment. As this technology continues to gain momentum and investment in the space increases, the need for machine learning talent will only increase. We’ll see an influx of candidates trying to market their relevant skills to hiring managers and ultimately, the talent supply will eventually catch up to the demand. But for now, the talent holds the cards.