A conversation on AI in the hiring space.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as Cadient.
Stuart Nisbet: I am the Chief Data Scientist with Cadient Talent. Our mission is to assist in the area of distributed hourly hiring.
My background is in computer science. I spent the majority of my career working in analytics and the application of analytics to a variety of different spaces. In the last ten years, we mostly focused on deep analytics in machine learning, which is referred to as artificial intelligence. We think of it more as augmented intelligence, at least, in our space of hourly hiring.
We also focus on some of the deep learning algorithms that try to assist humans in working on things that are uniquely human but can be assisted in terms of how we can apply path knowledge to make better decisions. That’s the theme of what we will talk about.
I have been in the industry for 33 years now. I graduated in 1987. I focused mostly on the computer science side in the application of programming in the area of analytics and machine learning. Cadient Talent is a relatively new company, but it has a long history. We acquired software from Kronos, which is a large company in the area of applicant tracking systems and distributed hourly hiring.
It focuses on large companies that have evergreen hiring. They are always recruiting and hiring for positions which means they always have attrition and turnover. We are trying to help them in that endeavor by providing better-quality hires. That doesn’t mean the quality of the applicants; it means the fit for the applicant for the specific job that you have.
We’ll talk a bit about assessment and how we can use assessments to determine that quality of hire. I don’t think this is novel in any way. We believe that if you have better quality of the hires and the fit for those hires, you decrease the turnover.
Turnover is something that is natural in any job, but it is costly, so you want to have the right kind of turnover. You want to have natural growth in the company, but if you could reduce the turnover for the people that you would like to keep, then you increase productivity and in turn increase profitability for the company.
In a nutshell, that is what Cadient Talent is all about. We acquired this software from Kronos because we wanted to apply very different skills to this area of hourly hiring and, in particular, distributed hourly hiring where most of our clients are. These clients could have 600 or 6,000 installations, so this distributed nature is quite important.
I joined the company as the Chief Scientist to try to bring some of the current practices of AI machine learning, deep learning, and algorithms based on past hiring decisions in order to make post-hiring decisions. That is a quick overview of myself and the company and what our mission is.