Improving the Relevance of Higher Education With Job Market Data—1Mentor’s Esteban Veintimilla on Teaming Up To Bridge the Skills Gap

Good morning, Esteban. Thank you so much for joining us on ETM Founders. As we were saying, I’ve got tons of questions—so, welcome!

Thank you, Laureano. I’m really happy to be here and talk through these topics.

Just to clarify before we begin: we’ll be talking about 1Mentor—not related to EdTech Mentor, which is a publication by 27zero. They’re completely separate. So, Esteban, let’s start with your background and how you ended up founding 1Mentor and joining QS.

Sure. I started working at the University of Waterloo in Canada, helping students land their first internships. I quickly saw two issues: students were lost, and universities weren’t preparing them with the skills companies were asking for. Employers would say, “I need someone who knows SEO or social media,” but students hadn’t learned any of that. I was also doing a master’s degree that the university would fund if I stayed for three years. I had 18 months left—but I realized I didn’t want to keep begging companies to hire unprepared students. I wanted to solve the root problem.

The University of Waterloo is known for having the best internship program globally—around 25,000 students go on paid internships each year. Since I studied mathematics, my instinct was to look at the data. We had about 120,000 job postings from the past eight years. I analyzed what companies wanted—for marketing roles, engineering, etc.—and saw clear patterns. I’d then help students fill those gaps by recommending specific skills and online courses. That hands-on approach led to a 680% increase in placements. That’s when I realized we could scale this.

And were those skills taught at the university?

Usually not, or they were taught too late—maybe in the fourth year, when students needed them in their first or second year. So we turned to outside courses. It was a great investment for students—they'd learn, land a better internship, and the job would pay back the cost.

And at Waterloo, students had to do several internships, right?

Yes, four to six, each lasting four months. It’s a co-op model—study four months, work four months. It’s common in Canada and Australia, but Waterloo really leads with that approach.

So you solved the problem manually—what was next?

I was also studying entrepreneurship, and part of the program was launching a venture. I partnered with Martín Serrano, my best friend from high school. We joined the Velocity Incubator, which told us: validate the problem. So we interviewed 70 universities—and in the process, three became our first clients: Purdue, the University of Alberta, and Waterloo.

How did you get those interviews?

We reached out with a clear purpose: “I’d love your perspective on how the labor market is changing and how you're adapting.” It wasn’t a sales pitch—it was a real conversation. That made all the difference.

That’s a classic engagement strategy—even if you didn’t realize it at the time. Listening builds trust.

Exactly. I didn’t know it was a “strategy,” but it worked. We needed to understand the real problem first.

So what did you find in those interviews that others missed?

Universities often say they “talk to companies” to stay relevant—but they usually talk to a few big names like Amazon or Citibank. But answers differ wildly depending on who you ask—even within one company. It’s not representative of the broader job market, especially in countries where most businesses are small or medium-sized. So we started analyzing data from millions of companies globally. That’s how we help universities align with real industry needs.

Let’s talk about your cofounder and early team—how did that come together?

Martín, my best friend from high school, was my first call. He’s an architect—not from the field—but incredibly disciplined. We also found a great intern from Ecuador through LinkedIn. Then, the incubator told us: if you want to raise money, you need a technical cofounder. So we called Diego Robles, another high school friend working at IBM. He quit his job, took a 50% pay cut, and joined us as CTO.

What high school was this? Sounds like it produced some amazing people.

[Laughs] Yeah, I was lucky to have good friends.

And the incubator—Velocity—what was that experience like?

Velocity is one of Canada’s top incubators. Their structure was super helpful. First, validate the problem. Then, build. Only after that comes funding. Once we validated demand, we raised $50K and used it to build our MVP. We also brought in more talent. One person, Andrés Cornejo—who had worked with NASA—joined us on stock options and worked nights. That’s how we got to a 12-person team and launched our prototype.

That’s amazing. What was the hardest part back then? You clearly had the talent to attract people—but what worried you most before the big funding round?

Getting to that round was my biggest concern. We attracted incredible talent—people from Mexico, Argentina, Ecuador, Venezuela—who joined even when we had no salaries. They believed in what we were building. We offered stock options, but that was still just a promise. What kept me up was making sure those who bet on us got something real in return. With the first $50,000 we raised, we could only pay about $400 a month—mini salaries. But it was a start. Every dollar that came in went to them. We needed real funding to invest in the team and keep going.

So the incubator invests first—then how did you figure out what kind of fund to look for? How did you learn to navigate the investor process?

The incubator really helped us structure everything—not just the interviews, but also the fundraising process. Coming from Latin America, we didn’t think in Silicon Valley terms. Our initial goal was to raise $150K. We started building a list using platforms like PitchBook, filtering for EdTech investors in early stages and across the Americas, since our team was spread between Canada, the U.S., and Ecuador.

Then something unexpected happened. A New York LP from the incubator’s fund wanted to meet us. The incubator told us: “Don’t ask for $150K—go for at least $500K or they won’t take it seriously.” So we changed one slide in our deck and pitched $500K. We didn’t get the investment, but the interest made us realize it wasn’t such a crazy number. From there, we started targeting top EdTech VCs.

And with that $500K—were you aiming to grow, or to reach profitability quickly?

We quickly realized it’s not about the number—it’s about the plan. At first, we thought: pay the team, build the MVP, get users, then raise again. But $500K meant more responsibility. At the time, we’d only analyzed 120,000 job postings. To be global, we needed way more. (Today, we analyze over 500 million.) We needed serious infrastructure to deliver reliable labor market insights to universities. Also, AI tools weren’t as accessible as they are now—we had to build everything ourselves. So that pre-seed round was to build a usable, data-backed product and start generating revenue. Our target was around $500K ARR to move to a seed round.

And being a marketing guy, I have to ask—was any of that budget for marketing or sales?

You won’t love this answer—we just hired our first marketing person a few weeks ago! Before that, it was just Martín, Diego, and me trying to do a bit of everything.

What about getting those first clients? You mentioned engagement marketing without realizing it—but what really helped retain them?

Relationships—100%. Not necessarily people we knew, but ones we built deeply and honestly. Early clients knew we were in beta. They gave feedback, helped shape the product, and stayed with us because of that transparency. To reach new clients, we focused on the basics: where do they go? What do they care about? We went to the right conferences, found early adopters, and built real trust. In two years, we were in six countries. Sometimes with just one client per country—but it was a start.

Can you recommend any events?

Two key ones. First, the ASU+GSV Summit—it’s huge in EdTech, great for both clients and investors. Second, the IFE Conference by Tec de Monterrey. We entered their startup competition, won, and they became our first Latin American client. 

My advice: figure out who your buyer is, and attend the conferences they care about. For us, that meant ones focused on employability and curriculum relevance.

You’re hitting on some great points. One goal of this series is to highlight lessons that may not be obvious—especially for institutions. Universities are complex, and roles like employability or academic relevance are often invisible from the outside. And conferences really are about relationships, not just content. Founders need to prep, know who they’re targeting, and have a clear strategy.

Totally. When we started, we just went because “everyone’s going.” Then we’d leave asking, “Was that worth it?” Now, we prepare. We book 20+ meetings in advance. Don’t just attend keynotes—you can watch those later. We go to meet people, especially universities willing to innovate. Pre-conference planning makes all the difference.

Alright—tell us more about QS and how 1Mentor fits into their bigger picture.

QS is best known for global university rankings—but only 6% of their staff works on that. The other 94% focus on solving problems in higher education. They work with over 6,950 universities across more than 90 countries. They saw what we saw: higher ed needs to evolve fast. Students need skills the market actually demands—real tools, technologies, not outdated programs.

That’s where we came in. They needed a data partner to help them understand global labor market trends. Now, we analyze over 500 million job postings and 283 million graduate profiles across 190 countries. If you graduated from a university in Colombia, for example, we can track your career path—first job, company size, industry, and more. It’s all data-driven. Our vision aligned perfectly with QS’s: you can’t solve the problem if you don’t understand it first.

Has your value proposition changed now that you’re part of QS?

We’ve definitely expanded. Our core offering was a platform that helped students identify career goals, skill gaps, and recommended learning paths—while universities got analytics on labor market trends. Now, with QS’s reach, we can go even further.

For example, one university asked us to help design an AI program—and they were using a textbook from 2011. We told them, “You can’t teach AI in 2025 using a 2011 book.” So we used our data to help them design something relevant. That’s where we’re headed—being both a foundational data layer for QS and expanding our own impact.

Makes total sense—especially in the education data space, which is QS’s core. Now, shifting gears a bit, I want to go back to the lessons. For other founders, it’s easy to think a problem just needs funding—or that you can bootstrap. Was that clear to you early on? And were there competitors?

Yes, it was clear. Some companies were doing labor market analytics, but the big gap was in making the data actionable. At 1Mentor, everything we provide has to drive action. If you tell a student software jobs are growing by 1.4%, what does that actually mean to them? We saw a huge need to make data usable—and for that, we needed funding. Analyzing millions of data points takes serious infrastructure.

For those unfamiliar with data at that scale—how do you even gather and manage 500 million job postings?

It’s a constant effort. We update our database monthly and pull data from three sources:

1. Large job boards like LinkedIn and Indeed.
   
   
2. Company websites with changing job listings.
   
   
3. Partnerships with universities and companies who share internal postings.
   
   

We started last year with 280 million postings—now we’re at 500 million. It never stops.

Zooming out, you see trends across industries. What excites you most—and what worries you?

What excites me is how data use has expanded beyond analysts. Marketers, legal teams—even they now need to be data literate. People are using data to make better decisions, not just relying on gut feeling.

It’s not just data science anymore—it’s about fluency across roles.

Exactly. The shift is real. But what concerns me is AI’s impact on the job market. For years we heard, “AI won’t replace you—it’ll be someone who knows how to use AI.” Now, that person might replace three roles. Instead of needing three hires, you need one. Entry-level jobs—where most people start—are disappearing. And if you raise the bar just to get in, education has to evolve fast.

And that’s already visible in job postings.

Yes. What worries me most is access. If entry-level roles are automated, where do people begin? It reinforces inequality. That’s why education needs to catch up—quickly.

Is that change easy to drive from inside universities?

Honestly, some universities told us, “If students see what they’re missing, they’ll realize we’re not teaching it—and that’ll discourage them.” That mindset blocks progress. But not all are like that. In 19 countries, we’ve met forward-thinking institutions using data to innovate, even if the short term is messy. They’re led by visionaries willing to drive long-term change. We just need more of them.

Let’s switch to investors—any red flags or mismatches?

In the early days, you feel like you should be grateful for any interest. But one VC told us: “You should also do due diligence on your investors.” At first that felt awkward—especially with high-profile VCs—but it’s smart. You want to know who’s on your cap table.

We didn’t turn anyone down, but we did take $25K from an investor just to smooth cash flow. They ended up being the most demanding—despite giving 10x less than others. They even wanted a board seat. Bigger investors didn’t ask for that. Same with clients: the smallest ones can cause the biggest headaches. You’ve got to be selective—especially early on.

Especially when you’re still moving fast—small misalignments can slow you down. Now, before the final question—how did it feel shifting from startup mode into a large org like QS?

We planned for that. During the acquisition, we said: “We’ll only move forward if we report directly to the CEO.” We didn’t want to be buried under layers of management. QS had two divisions—Student Recruitment and Institutional Performance. After we joined, they added a third: 1Mentor. From 1,000 employees, we were just 20. But that structure gave us agility. We make decisions and report directly to the president or CFO.

That said, big companies are different. If I want to give someone a raise, I can’t just approve it. There’s benchmarking across countries, roles, and experience—it’s a full process. So yes, you get the support of a big org, but also all the red tape.

Fair enough. Can I ask—who came up with the idea to negotiate direct reporting to the CEO and become a strategic arm of QS?

That was a group decision between my co-founders and me. I honestly don’t remember who suggested it first—but whoever did, great call. We knew we’d need speed, especially as an early-stage team. If we were already doing $15 million a year, maybe it wouldn’t have been necessary. But at our stage, agility was key.

Totally. I know we’re over time, but here come my final two questions. During the acquisition, was there a moment when you thought, “Maybe I’m not ready for this”?

Definitely. The process took six months of negotiation and due diligence. Early on, I thought, “What if this falls through?” It was eating up time and energy. Around month three, I told my co-founders I needed to step back from the deal to focus on operations—because whether or not it closed, we still had to grow.

Another big challenge was the legal side. A Canadian lawyer quoted us $70K for support—way too much for a startup. Meanwhile, QS had a full team: Deloitte, BDO, lawyers across countries. The power imbalance was clear, and we had to figure out how to navigate that. We weren’t fully prepared—but we held our ground.

That sounds exhausting—but you just described it perfectly. It’s high-stakes, and you can’t let everything ride on it. Were you and your co-founders aligned on the offer?

Yes, financially we were very aligned. From the beginning, we set a floor and said we wouldn’t consider anything below it. When the offer came in above that, we said: “Here are seven conditions. If you meet them, we’re in.” They went point by point and addressed them all.

What did come up were personal circumstances. That part doesn’t get talked about enough. We were the lowest-paid people on the team—I was making $1,200/month, and one of my co-founders lived in London. It was tough. We had to step back and say, “Let’s be honest about what we each need—not just as a company, but as people.”

That’s a powerful point. A lot of founders don’t realize how much leverage they actually have in these deals—especially when the acquirer needs the acquisition, not just wants it.

Exactly. You have to signal that you know your worth. Define your boundaries ahead of time. What we didn’t know during the process—but later learned—was that QS had evaluated 16 companies before choosing us. They spoke with startups in the U.S., Singapore, and beyond. If we had pushed too hard, they might’ve walked away. But we were clear, and they respected that.

Right—strategic acquisitions are rarely impulsive. And that insight is gold for founders going through it. Now, last question. Founders today have way more tools than we did. If someone’s launching an EdTech startup today, what three things should they keep in mind?

First: invest in relationships. Not just with clients—but your team too. Some of the people who worked for free early on now lead our machine learning division. Clients who saw us stumble in the beginning stayed with us, and even brought us into new institutions or government projects years later. Relationships are everything—especially in education, where people move between roles and organizations often.

Second: talk to users before building. Interview potential clients. Don’t sell—just listen. What’s their pain point? How are they solving it now? Is your idea actually better? Their answers will shape your product way more than your assumptions will.

Third: focus on what moves the needle. There’s always too much to do—website, product, hiring, sales, fundraising… You have to learn to prioritize. Every day, ask: what’s the one thing I can do today that’ll have the biggest impact?

That’s not just a startup tip—that’s life advice. So now you owe me three bonus startup tips next time! But seriously, Esteban, anything else you’d like to share before we wrap?

Just a big thank-you to our team. You’ve asked about the early days, but the truth is, we wouldn’t be here without everyone who’s joined along the way. People who believe we can truly change education—and show up every day to make it happen. They’re the real reason we’ve come this far.

That’s a perfect note to end on. You even told me before the interview that you see your whole team as co-founders. Esteban, thank you so much. I could go on for hours—but let’s save it for next time. Wishing you and the whole 1Mentor team all the best at QS.

Thanks, Laureano. I really appreciate it—and this series you’re doing. I’ve learned a lot from others’ stories here too. Hopefully this helps someone else on their journey.