Hiring Top Tech Talent

Hiring top tech talent is hard, especially when these people are in high demand. So how can you build your tech team? HR and hiring experts Laura and Theo talk about their process.  

Laura Ianuly: I think the most important thing, the best advice I could give a hiring manager is making sure that they understand what they’re looking for. They’ve defined it, and they understand it. Secondly, being certain that they recognize it when they see it. And then thirdly, they act. So the failure to do those three things well is going to have an inferior recruitment process. And it’s going to impede your ability to build the team as quickly as you need to.

Ginette: I’m Ginette,

Curtis: and I’m Curtis,

Ginette: and you are listening to Data Crunch,

Curtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world.

Ginette: Data Crunch is produced by the Data Crunch Corporation, an analytics, training, and consulting company.

Ginette: If you want to become the type of tech talent we talk about on our show today, you’ll need to master algorithms, machine learning concepts, computer science basics, and many other important concepts. Brilliant is a great place to start digging into these. 

The nice thing about Brilliant is that you can learn in bite-sized pieces at your own pace, and with a bit of consistent effort, you can tackle some really tough subjects. Their courses have storytelling, code-writing, and interactive challenges, which makes them entertaining, challenging, and educational. Sign up for free and start learning by going to Brilliant.org slash Data Crunch, and also the first 200 people that go to that link will get 20% off the annual premium subscription.

Ginette: Now onto today’s show.

Laura: I’m Laura Ianuly, the founder and CEO of Ianuly talent accelerators. We provide HR and recruitment strategy for venture-backed startup companies across ad tech, FinTech, health tech. We’re based in Seattle, Washington, and in New York. Prior to founding this business, I was the global head of HR and recruiting at DoubleClick. I joined as employee 70, 75. And when I left, we had over 1,500 employees and had gone public. And at the time it was the most successful IPO in New York.

Curtis: That’s awesome. And how about you, Theo?

Theo: Uh, my name’s Theo Ianuly. I’m the COO, CMO. I’m based out of the Seattle office. And three years ago, Laura brought the opportunity to me because Laura was growing at a rate where she needed help to continue to reach new audiences and reach new verticals in the startup space. So in the past three years, we’ve grown, and we’ve started to work with startups not only in Seattle, but New York and beyond.

Curtis: That’s awesome. And so you guys see a lot of startups. I’m assuming a lot of these startups are in the tech sector. They need data teams. They need people who can do machine learning and data science and all these kinds of things. And the word that people hear is that there’s a big talent crunch with these kinds of people. They’re hard to hire. They’re hard to keep, and you guys live in this space. So, so maybe you can give us a street view of what this looks like practically for companies and how they’re navigating.

Laura: Absolutely. I mean, there is definitely a war on talent. I think anybody who’s looking for a job feels it because they’re bombarded with calls from prospective clients needing to build their teams or recruiters, and they just have, you know, the pick of the litter. And I also think from the client side, it’s just a real pain in the neck to build their teams because there’s so much, there’s, there’s so much demand in such little supply for really great top talent out there. If you look today at what’s happening in supply and demand specifically for data science and machine learning talent. I mean, today, there are 27,000 plus open data science roles in the US, and there’s less than 10,000 people looking for jobs that are data scientists, and also for machine learning/AI, in the U S today there’s over 50,000 openings for machine learning/AI talent. And there are only 3,600 people looking. So that’s the problem that we’re in right now.

Curtis: Sure. So, given that, that’s the landscape, it’s difficult to find these people, how do you approach it? How do you help people find talent, hire talent? You know, where do you start?

Laura: A couple of different approaches? Okay. The first thing that we will always do is go out and meet with our clients. And because we’re working with startups, oftentimes when we meet with the VCs to get a better understanding as to why they made the investment in this idea, in this product, in this service. So oftentimes, every time we have a conversation with a candidate for one of our clients, it’s an upsell. It’s not as simple as saying, “I’ve got an, a data science job at Google, or I’ve got a data science job at Oracle.” So every single discussion is an upsell. So we’re not just selling the product or the service, but we also need to sell the management team, the executive team, their track record of taking a business public of successfully championing an exit, whether it’s an acquisition or going public. That’s how we, that’s exactly how we start.

We have deep-dive discussions in our kickoff calls with clients to find out exactly what our hiring managers looking for, data science, machine learning, AI, that’s a function it’s new, it’s growing. Everybody wants to incorporate that technology into their product, but what’s the product? Is it a, you know, a B2C product? Is it a B2B product? Is it an e-commerce product? Is it direct to consumer? Understanding that the engineers and the data scientists that they’re looking for have an understanding of the product, the fundamental product and the industry it plays in is important.

Curtis: Right, so domain knowledge you’re finding is, is very important for, to the success of these people, joining the teams. Is that correct?

Laura: Exactly. That’s exactly it.

Curtis: Okay. So domain, knowledge is one thing you kind of look for, and when you are building out these teams, I know everyone has different products, different industries, but is there a typical structure you look for in starting to hire a data team? Meaning would you go for someone who’s maybe a really good communicator and a good leader first, and then hire the, you know, a data engineer under them and so forth? Or how do you structure this well?

Laura: So when we’re brought to a company, usually there’s somebody, somebody working in the data function. A lot of our CTOs, a lot of our founders have technical backgrounds. So at an initial standpoint, there’s a point person, whether they’re contract, whether they’re full-time, whether they’re a consultant or advisor, somebody’s in that role. When you’re building out a team, a lot of critical decisions get made. Are you going to hire your team off shore? Or you’re going to hire them here? Are you going to be able to compete with top talent, right within your marketplace? Ninety-nine percent of the clients, I think, start from the top down, they look for a strong technologist that also knows how to build teams and distribute workloads.

Curtis: Okay. So that’s kind of the first one. And then what does the process look like? So you made the decision to make a hire here. You’re kind of looking for these people. There’s a lot of ways you could approach this. Recruiters are throwing stuff up on Indeed. And then you’re looking at GitHub profiles and doing the interviews. What questions do you ask? Can you take us through the process of doing this well?

Laura: Sure. Um, the best hiring managers are the ones that make recruitment a key strategic initiative for their business. It can’t be something that you try to do on the side. It’s, as we said earlier, it’s just too competitive. So the right way to go about it is to set up a weekly touch base meeting with our team. We are on the hook to deliver the top talent that our team has recruited since last week’s touch base recruiting meeting. We pitched the top candidates to the hiring manager, and they start the interviewing process. Next week, we start to debrief them on the people that they interviewed, and it’s a constant force ranking of the people that they interviewed. And if there’s a lot of . . . there’s a lot of self-discovery that goes on from the hiring managers. And sometimes they might be pivoting or redefining or asking us to look in a different area.

So we continue to refine the process of what we’re looking for throughout these weekly touch-base meetings, so that we are targeted and honing in more on what the client’s looking for. Once we identify candidates, the hiring manager is interested in, they certainly will want them to meet people on their team to see if they fit, if they can collaborate, they want additional inputs. Sometimes these interviews involve a case study. Sometimes they involve a technical test exam, but more often than not, our clients are not looking only at their technical skills. They’re looking at their ability to program and code and contribute to a team of people doing the same activity.

Curtis: Interesting. And how do they, how do they effectively judge that that’s a, it’s sort of a mix of hard and soft skills. How do they go about figuring out who’s good at that?

Laura: It’s process of elimination. Like a lot of hiring manager . . . there’s a great diversity, in my opinion, of hiring managers in their level of experience in hiring. I think the most important thing, the best advice I could give a hiring manager is making sure that they understand what they’re looking for. They’ve defined it, and they understand it. Secondly, being certain that they recognize it when they see it. And then thirdly, they act. So the failure to do those three things well is going to have an inferior recruitment process. And it’s going to impede your ability to build the team as quickly as you need to.

Curtis: And maybe on the flip side, too, it’s an interesting question. If you’re someone who is looking for a job, obviously you have a lot of opportunity, but what is the most important for them? Is it, “I have a really good GitHub profile.” Is it, “I’ve been to an accredited university.” Is it I’ve taken these certifications online? What’s the most important thing they can bring to the table?

Laura: Oh, I love that question. I mean, we, my team and I, we believe that we’re like agents to the tech talent out there. We stay very close to top tech talent, and we want to be the people that they refer to over and over when they’re conducting a job search. I mean, Michael Jordan wouldn’t do a deal with Nike without an agent. And right now the supply and demand has made these top tech people in the States like the Michael Jordans. So I think it’s very important for these top talent technologist to have representation, representation that knows the client knows what they’re looking for. Preferably has a history with the client, has placed other people into that company and can reference what those new hire experiences have been. And that can just prep the candidate and debrief the candidate. Failure to do that is not going to align for success.

You know, these kinds of deals, they just don’t kind of roll over the finish line on their own. They need to be managed. And also you’ve got to declare . . . if you’re a candidate and you’re going on an interview and you know what you’re looking for when you’re in that interview with a client, declare that you’re interested, let them know this is something that you want to do. Let them know that you’ve interviewed with a bunch of other companies, but this is looking like the number one that you’re interested in doing. It’s not inherently a part of the personality of an engineer that might be a little bit more cerebral and introverted. So we try to encourage them to do that.

Curtis: Right. Show, show your interest. I was reading an article the other day about the university degree is dead or whatever for the tech space. Do you feel like that is starting to be more true or still an important aspect?

Theo: When we’re in the process and we’re, we’re out there looking for candidates, it really depends on the hiring managers and what they’re, what the attributes are that they’re looking for. So sometimes we’ll find candidates who have a wealth of startup experience, and that brings its own value to the table. Other times, when we do have hiring managers that are very focused on the educational aspect of the candidate, and then we might have another client partner that is really focused on, did that candidate have experience with one of the big companies that are really pushing the envelope on machine learning and AI. Is it Google? Is it Amazon? Is it Oracle? Or Microsoft? So it really depends on the hiring managers focus.

Curtis: So you kind of see a mix still. So, so once you have, you know, you’ve gone through this whole process, you’ve hired some great people to work and help you in this space. How do you then retain them? Because one of the other problems I often hear is people don’t stay in jobs ’cause again, like you’re saying, they have all of these recruiters constantly trying to pull them away to other opportunities. How do you keep talent at your company?

Laura: It’s a great question. So I think that companies are in different modes with their tech, like all companies or in different modes. So some are in fast growth mode and some are a little bit more in maintenance mode. The world that we operate in is super fast growth mode, right? Because they’re trying to really get there, get their product out, get a user-base on board. So different technology candidates, kind of excel at different phases of the process. There’s some people that are just amazing with companies that are going from, you know, a million to 25 million in revenues. And if the company gets big, like over 200 people, some technologists are just like, they just want to go right back into the early stage. So there’s different stages of companies. And in the stage that we focus on is that earlier stage. And so we’re constantly looking for candidates that have experience in that stage. So the retention question that you ask, what I get a lot is, if a technologist has worked at a company for two or three years, and that company has really grown and been successful, we’ll get a call saying, “find me exactly what I’m in now, but three years ago, I want to do it again ’cause that’s a fees that I love.

Curtis: So it even depends on the phase of the company. People are really good at certain, you know, maintaining or building or these kinds of things.

Laura: 
Exactly.

Curtis: That’s awesome. I’d love to hear if you could share with us one or two concrete examples of companies you’ve actually worked with that have gone through this process so we can sort of see how it worked for them.

Laura: So we had a company 33 across that we worked with. They were a technology publisher, SAAS based tool. They were on a massive growth trajectory based here in New York. And their CTO was based in Sunnyvale, California, like a super sharp guy with a lot of experience. And we took the team from about six or seven to over 25 in less than a year. They were constantly, um, this is what I really respected about this hiring manager. He would meet with me quarterly to present to me the product roadmap so that my team and I understood the contributions that the people that they hired through us were making and how they were continuing to grow in the kind of new skill sets that they would need throughout different phases of the company. And it was successful. I mean, we had four full-time recruiters on my team looking for people.

We were successfully able to convince them to consider hiring remote talent. That was a significant milestone and provided them with the ability to grow faster than they would have been otherwise, I don’t know the details of exactly how, but this CTO had an exceptional retention on his team. People were not leaving. People were constantly growing in their role. People were rotating in jobs, um, on the tech team, it just was a very, it was a, just a, a high touch point, I think, collaboration between us and the client. It was just, it was great. It was a good situation. Would you like me to share a story from the other side, like from the candidate side?

Curtis: Sure. Yeah, that’d be great. Great.

Laura: So there was a candidate, a number of years ago that I hired into a CTO role for a startup company. And we worked together within this company for about a year, and he did some great things. The company grew quickly and we both left at about the same time, and he was looking to go back again to a very early stage company to start to pull together the roadmap and develop out the engineering team. So this individual over the past five or six years has not only just been a client and then a hiring manager, a candidate rather I meant to say, and then a hiring manager, but they went back to being a candidate again. And just two months ago, he’s now a hiring manager. So it’s interesting when you develop that relationship, because I know when he says, “I need somebody, who’s got like some street smarts. I don’t care about education, but they’ve got to have worked on a team successfully.” So I kind of know him and know what he means and it makes, makes it a lot easier.

Ginette: Thank you to, Laura and Theo, for being on the show today and as always go to data, crunch Corp com slash podcast for our transcript and attributions.