What Recruiters Should Know About Hiring Data Professionals

The Recruitment Hackers Podcast

00:00:01.860

Max: Hello, and welcome back to the Recruitment Hackers Podcast. I’m your host, Max Ambruster and on today's show, I'm delighted to welcome Tim Freestone, who is the founder of Alooba, a tech startup based in…well Tim is based in Australia, but I gathered your team is spread out all over the world, which is specialized in helping companies, hire data scientists, engineers, architects and analysts, and so all the people that deal with data. And if you live in the same world that I do, that share of the employment workforce is always growing, and every company needs them. So, I'll be asking Tim about how to attract and how to interview this talent, and welcome to the show Tim.

00:00:56.220

Tim: Thanks for having me, Max. It's great to be here from a very sunny afternoon in Sydney.

00:01:01.890

Max: Great! Great to be connected. So Tim, tell us a little bit about yourself to begin with. How does…how did you end up in the…or maybe we'll start with your company, Alooba. Did I describe it okay? Is it an attraction methodology? It's more of a screening methodology or tool, right?

00:01:26.820

Tim: Yeah! So we basically assess people skills in analytics data science and two main use cases for that. One is definitely that hiring use case which you mentioned and so companies would use our product typically either as a very short initial screening quiz that they would send to every applicant who applies for one of their data roles. And there'll be a customized assessment on our platform assessing things like ,I don't know, statistics machine learning visualizations, really depends on the role. And that's kind of one half of the company. The other half is really around assessing people skills internally within a business trying to find the strengths and weaknesses. And that's most often being used in conjunction with the data literacy strategy. So it's becoming bigger and bigger these days that you know, you might be a data scientist and have really advanced skills, but what about the 99% of the company, who aren't data scientist? What kind of data skills do they need? And so a lot of businesses realize that everyone needs some basic data literacy. And so we often get involved at the starting points of putting in place that learning and development plan. We really come in as that measurement tool to understand okay what's our current benchmark, and then keep measuring through time to see hopefully that they've had some improvement in their data literacy.

00:02:44.100

Max: Hmm! Yeah, makes sense. I was advised for my business to put a portion of our account management team on things like learning how to use SQL and I'm getting training like that, so I guess I've put it out to my employees as a good recommendation but I haven't enforced it, but you know in bigger companies you're seeing data literacy being enforced at the corporate level and pushed across departments. Is that an example? Like an SQL training?

00:03:18.660

Tim: I'd say SQL would probably fit into the relatively advanced part of data literacy. So they'd be things that are even more basic or simple than that would normally form part of that program. It could be things like, hey, you know what metrics should I be looking at to answer these types of problems. Understanding basic ideas around like sample size. So, you know if you're reading a report and you see that I don't know the number of bookings in England went from… went up by 50% but you know, to look at that and actually they went from two to three so that doesn't really mean much if the book has gone from two to three right? And just having that kind of understanding of the basics of data, really.

00:03:58.800

Max: Yeah! I suppose there is such a wide gap between, you know, the experts and the beginners that you gotta lift people so that they don't say anything stupid to begin with, like use two decimal points on a percentage when your basic…like you said on a sample size of two or three, stuff like that. Great! Well, how did you end up, you know, launching Alooba. I suppose this is a problem that you…it sounds like this is something personal, apparently, that you want to do for yourself.

00:04:34.950

Tim: It definitely is a selective confluence of the last 10 years of my life, really is this business. So, the last role I was in was at a tech company, I was leading an analytics team. And so, I noticed two big themes, while I was at this business, so one was anytime I went to hire any kind of data professional, so, data analysts, data engineers, data scientists, I found it personally a massive pain in the ass trying to hire. So, the process was you know you put up a job ad on LinkedIn or in Australia. We have seek like the big job platforms. You get all these applications through and you basically get a CV. And then from that CV trying to pick through quickly and figure out, who are the best candidates to interview.

What I found consistently was that it was very hard to predict, based on a CV alone, who the best candidate was to speak to. So, that meant that I have to do a lot of interviews to hire one person. I'd often get five minutes into an interview and realize the candidate who said they had X, Y said advanced skills, obviously didn't have those. And so, I really wanted a more efficient, simple, a more objective way to screen candidates that was one origin. And the other piece was looking around at my colleagues and realizing that in a company of 150 people, we had maybe I think six or seven data professionals. But then, there are at least another 30 or 40 people, all the product managers, all the online marketers, the senior managers of the business where I looked, what they actually did day to day, it was basic analytics, even if they didn't think of themselves as analysts. And it was very clear to me that this data literacy thing was becoming more and more important.

00:06:10.230

Max: Yeah, yeah! So, it's like…it should be like a mandatory step in the journey for a good portion of the job be…well, can you handle data? Do you know how to extract it? How to use it? How to interpret it? That makes sense and the other point you made, which is you know the resumes are lying, right? That if you look at a hot space like the one you're in where it…we know that salaries are inflated and that there is not enough talents, and so it's going to potentially attract people who are trying to find a shortcut to a better life, you know and good. But I will guess there are some resumes that are kind of like packed with keywords that don't belong there.

00:06:54.600

Tim: Yeah! There's definitely some keyword stuffing. There's some inflation there's also just… you know, we're not the best judges of ourselves, and a really interesting data point that we collect directly on Alooba to kind of master this is that, before a candidate starts a test, they rate themselves on a scale of one to ten for each skill that we are about to assess them in, and then we compared their self-rating to their actual performance to come up with what we call the self-awareness index, and to cut a long story ...