Christina Qi, SB ’13

Christina Qi, SB ’13, is the co-founder and CEO of Databento and the first undergraduate Sloanie to appear on this podcast. Her path runs from day-trading out of a Harvard dorm room, where her HFT firm Domeyard peaked at 25,000 trades a day, to founding Databento and nearly losing it: a bridge round raised with almost negative runway, investors who signed financing docs and never wired, and finally a $97M Series B that made it all look inevitable.

The heart of the conversation is what Databento actually does and why it wins: harmonizing market data across exchanges so that, in her phrase, "all the books are in one language." Qi is candid about the industry’s lack of competition, customers who leave over price come back, she says, because there’s nowhere else to go, and about what the product still lacks. She also takes aim at AI hype ("maybe this is why I hate AI": companies incorporated today claiming $100M ARR by November), and explains how AI data-center demand priced her disaster-recovery site out of Utah and into Portland.

Woven through is the Sloanie thread: serving with host Christopher Reichert on the MIT Sloan Boston Alumni Association board, getting a C-minus in Bob Merton’s class, and the parents who came from China and settled in northern Utah. It closes on her definition of success, the number of hours you can spend doing the thing you truly want, without consequences.

Listen to the Episode

Read the Transcript

Christina Qi: Success is the number of hours you can spend, or afford, to do the thing you truly want to do during the day, without consequences.

Christopher Reichert: Welcome to Sloanies Talking with Sloanies, a candid conversation with alumni and faculty about the MIT Sloan experience and how it influences what they're doing today. So, what does it mean to be a Sloanie? Over the course of this podcast, you'll hear from guests who are making a difference in their community, including our own very important one here at Sloan.

Christopher Reichert: Welcome back to Sloanies Talking with Sloanies. I'm your host, Christopher Reichert, and today I have the immense pleasure of talking with Christina Qi. If I'm not mistaken, she is the first undergraduate Sloanie on this podcast, and she sets the bar very high.

Christina earned a Bachelor of Science in Management Science from MIT in 2013 and earned her Chartered Alternative Investment Analyst designation in 2015. We briefly served together on the MIT Sloan Boston Alumni Association board in the years before COVID, so this feels like a reunion for me. Before we go any further with my introduction, let me welcome Christina to Sloanies Talking with Sloanies.

Christina Qi: Chris, it's so good to see you again and to chat with you today. It feels like a reunion, finally. It's really good to see you.

Christopher Reichert: It's great to see you. And there's so much to cover in the years since you left MIT, so I'm just going to race through some of that to set the stage, so we can start our conversation.

Christina is the CEO and founder of Databento, one of the fastest-growing providers of financial market data in the world. The company was founded in 2019 and has fewer than, I think, 30-35 employees. I know you're growing, and you recently closed a Series B round of $97 million. The success of Databento has been well covered in many articles and some great podcasts, I really particularly like CNBC's Fortt Knox with Jon Fortt.

In short, Christina set out to solve a persistent pain point, which is acquiring quality market data from vendors. I really love the name, too. It's clever, if you've ever eaten a Japanese bento meal, you get it. Small portions, segmented cleanly. I really love that. It's a nice visual.

Before that, Christina founded Domeyard, a high-frequency trading firm, out of her dorm room while at MIT, along with two other students, one at MIT and the other at Harvard, hence the name. Over the course of its almost decade of existence, it grew to trading $7 billion a day, which I want to understand a bit more about.

So, if you don't know what high-frequency trading is, I'll just go through it, and Christina, please correct me. Domeyard conducted huge numbers of statistical arbitrage trades, using sequential learning in a high-frequency trading context to make statistical driven trades, seeking out a small edge on each trade and then making a large number of trades. They used technology to search for all sorts of signals that could trigger a trade, like speed, or load of the market servers, to gain an advantage. I mean, of course, right?

So, did I get that right in terms of what high-frequency trading is? And then tell us how that started up, and about the winding down of it, because I find that fascinating.

Christina Qi: Yeah, for sure. You're pretty much correct. High-frequency trading, the best way to describe it is it's really just trading a lot, trading at really high frequencies. To give you a sense, at our peak we traded around 25,000 trades a day.

The good part about what we did was that by the end of the day we knew how good or bad we did. If you trade 25,000 times, you know exactly how awful or how good you are skill-wise, because you can't get lucky 25,000 times.

So, we were just placing lots of trades. Obviously, those are machine-driven, 100% automated strategies. We would have to look at a lot of data, and that data would have to be machine-fed as well, so it would have to be very granular as a result, and so we would have to look at what we call level-three order book data, think of it as a 3D view of all the trades coming in, all the bids and offers coming into the market, rather than just the top of book, which is historically what a lot of hedge funds used to look at. So, we looked at a more granular view of a lot more data than usual, and we were making a lot more trades based on that data, a lot faster and at a lot higher frequencies than most folks out there.

That's what we did for a while, until we reached a point in this space where, you might have heard of this, there was a latency race to zero. Zero latency, where you basically get to almost the theoretical speed of light, or as close to it as we could possibly get, where becoming one nanosecond or one microsecond faster really isn't going to make that big a difference. The cost-benefit analysis, the ROI, is not quite there anymore.

So, we just called it. We're theoretically pretty much almost at the speed of light. Over the course of that decade, as we were building out the fund and building out the strategies, we, as an industry, hit that theoretical limit. And suddenly it didn't actually make sense to pursue HFT anymore. That's why you rarely hear about high-frequency trading these days.

Christopher Reichert: Was it basically a race to the bottom, but in this case, the most efficient, and it became a commodity, in the sense that everybody could do it?

Christina Qi: Exactly. It became very commoditized.

So, in Michael Lewis's book Flash Boys, which helped bring high-frequency trading to the public scene, so it helped everyone learn and understand what it was, yeah, there are a lot of inaccuracies in the book, but at least it helped the public understand and hear about the term. It describes how all these early HFT firms would blast holes through mountains, tunnels under the river.

Christopher Reichert: I've heard about that. Carving miles off.

Christina Qi: Yeah, exactly. Microwave towers, right? To get the fastest speeds. And cables across the cities, whatever, to get the fastest speeds. But now those paths, the fastest routes between, say, New York and Chicago, are owned by vendors. So even for us, we would pay a vendor a flat fee, maybe $5,000 a month, and we would get the same speed as the next fastest company.

In case you're curious why: I don't know if you know this, but a lot of U.S. equities don't trade on just one single stock exchange. There are different stock exchanges in the U.S. that trade multiples of them. So, if you can have an informational edge, if you can trade faster, or get information faster between locations and transmit that information faster, you can have an edge. That's what encouraged the early beginnings of high-frequency trading. The faster you can transmit that information between these locations, the better.

That's always happened in history, to be fair. If you go back in time, the Pony Express transmitted information from the East Coast to the West Coast, but that was proliferated because people wanted to transmit stock price information, for the most part. That was the reason why the Pony Express became so-called profitable at the time. And then that quickly got replaced, also because of transmitting stock price information. And before all of that, it's carrier pigeons. The pigeons are transmitting this kind of information. So, transmitting information about the financial markets has always helped boost these kinds of technologies.

And is it good? You can argue back and forth about the ethics of it, whether it's good or bad, front-running, et cetera. But how can you have an edge in the market? You can have an edge by predicting where the markets will go next. And how do you predict where the markets go next? Machine learning, AI.

So now we're in this AI era, which I find actually pretty exciting, even though, as much as I hate AI personally. I hate it when I see social media posts written by ChatGPT. I hate that too.

Christopher Reichert: There's a certain genericness about it, right? AI everything. If you look at so many companies, it's like you just put AI at the end and it's, oh, okay.

Christina Qi: Yeah, I agree.

Christopher Reichert: By the way, you say you are not an AI company, Databento.

Christina Qi: Yeah, we're not an AI company. And to be honest, I'm kind of proud of that. We've gotten this far as a company, as a startup, and we're not AI. We've raised this much funding and gotten this far, at such a high valuation, without being AI, in this era. As a startup, to be able to get this far in this AI era, I am pretty happy with that.

Christopher Reichert: But you've been at this for a long time, 13, 14 years since you graduated. I was reading an article you contributed to, about how artificial intelligence is transforming the financial ecosystem, back in 2015. That was long before AI was in mainstream thinking. That's 11 years ago that you were contributing to discussions about artificial intelligence.

My question really is this: what is it about you, or your education, or your mindset, maybe, that gives you the ability to see through the noise and understand what matters, whether it's technologies, platforms, systems, so that you can say, "Well, AI is buzzy right now, but it doesn't matter to what we're doing, because it's not really what we're about"?

Christina Qi: I think it's just more important to see things for what they are. It's actually true that in finance we've talked about AI for decades, it's not a new thing in finance. But it is actually true that AI has actually taken off in finance in recent years. That is something that is true. You'll see a lot of financial firms buying up GPUs in recent years. That's a fact.

NVIDIA has that conference, what's it called, GTC, every year, and Jensen gives this keynote talk and he says the biggest consumer of GPUs is now financial firms. That scares me a little bit. But it's true. So financial firms are now really consuming a lot of AI technologies behind the scenes, because it's profitable for them. So, it is true that it's finally happening.

I guess the question is: why was it not profitable back then? I think it's just understanding what's hype and what's good, what's bad. Maybe one of the lessons learned there is that the human is the most complicated machine, and that no matter how much money you put into AI, it's hard to predict what human behavior does. Humans are so unpredictable, and a lot of times AI just fails to predict these things.

So, AI does have weaknesses, and it's good to acknowledge that. That said, I'm not always anti-AI, AI has a great place in the medical field and science, there are awesome use cases. But I do see a lot of people who start AI companies for the sake of starting an AI company, to raise a lot of funding, just for the sake of doing AI.

To be fair, nowadays, if you were to start a hedge fund today, well, what else are you going to do? You can't compete on speed anymore. You pretty much have to compete on being intelligent in some way, shape or form, predicting where you think the markets are going to go next. And you kind of have to use some machine learning or some AI, or have an informational edge, which means you have to have some unique source of data. And that's hard to do. What else are you going to do? Otherwise, how are you going to succeed in this world?

Christopher Reichert: So, I want to talk about some of the influences in your life. It seems like your family is a huge influence, your parents, and what they went through coming from China and settling in northern Utah.

Christina Qi: I literally live 10 minutes away from my parents now. My brother lives with my parents. So, I live really close to my whole family, which has been super nice. I moved back during COVID, so now I live really close to them. It's been really nice. They're definitely a big influence on me. My mom sends me lots of crazy articles all the time.

Christopher Reichert: Yeah, my mother too. 96 years old, and by the way, coming back to the Fortt Knox podcast, how did you do in the jigsaw puzzle competition?

Christina Qi: Oh my goodness. The funny thing is, I actually messaged him, because he asked me how it went. That was the first tournament that we got first place in. And I'd never won a jigsaw puzzling tournament.

So, for those of you who haven't heard it, I was on an interview called Fortt Knox, and I was talking about how I do these jigsaw puzzling tournaments. I don't know if you know it, it's called speed puzzling. You sit at a table of four, and it's supposed to be fun, they're at bars, so it's a fun event.

Christopher Reichert: You grab a group of four.

Christina Qi: Exactly, you grab a group of four, and you're supposed to order drinks, it's supposed to be chill. Everybody gets the same jigsaw puzzle per table. You open it, the puzzle pieces spill all over the table, and you're supposed to complete the puzzle together in the shortest amount of time.

And I was saying our group has never actually won. We just do it for fun, because it's fun and exciting. We've done this sometimes, whenever I'm in Utah, I'll try to attend one and just go, because it's nice to have a routine. And then, hilariously enough, that week, by whatever coincidence, we actually won for the first time. I was so happy, because I've never won ever. So that was the first week we've ever won.

Christopher Reichert: And I remember you talked about how your role was the edge pieces.

Christina Qi: Yeah.

Christopher Reichert: Get all the edge pieces in. I don't know how complex these puzzles are, but I think I would probably take that same role, because at least you have one defined edge, right? It's straight or curved, it's not crazy.

And I was thinking about how your roles at Domeyard early on were also really well defined. Your partner Lin was responsible for the trading strategies. And did I read this right, that before you guys partnered up and started Domeyard, he was trading Euro stocks and getting like 2,000 euros a day in profit, just out of his dorm room?

Christina Qi: This is crazy. I feel like we go really far back, because no one remembers all this stuff. I feel like we probably talked about this at some point while we were both on the Sloan board, or whatever it was.

Christopher Reichert: That's a crazy amount of money just to be day trading, I guess. And then your other partner, Wang was for the technology, and then you were the business, including the fundraising. And is that how it is at Databento right now as well, for you?

Christina Qi: Yeah, I do a lot of the more business-y stuff. I would never call myself a quant or a technical person whatsoever. I do a lot of helping with the hiring, helping with the fundraising and stuff, keeping things together, hopefully.

Christopher Reichert: So how do you manage that team, the team dynamics, with your co-founders, on the vision, or get motivated by them? It's more of a behavioral question than a technical one. Just keeping all of you on the same path for the vision, or evolving, without exploding.

Christina Qi: To be honest, I feel like the whole team keeps me involved. I think we're really lucky with that. I've talked with a lot of other founders where they feel like, let's say on a team of 12, "Oh, it feels like only two people do the actual work and everyone else just kind of follows along." Whereas for us, everybody feels equally, amazingly productive. We get the feeling that everyone does an amazing job. No one's quit the company in ages and ages. I don't even recall the last time someone quit.

We've also had the chance to sell Databento. A lot of data companies tend to sell around our stage, Series B. And we chose not to sell, because I was like, well, I don't want to bail when our team doesn't want us to. Our team wants to stay. I feel like everyone would be really sad if we got bought out by a bigger company.

And it feels like we haven't started, the product hasn't even, we don't even have a complete product yet, by the way. We're a market data company, but we only sell data, mostly U.S. data: equities, options, futures, and that's it. We don't have FX, we don't have fixed income, we don't have crypto. We're missing tons of asset classes, and also geographies. So, our product's not even complete.

Christopher Reichert: That was a theme I saw between Domeyard and Databento, maybe that's a barrier-to-entry component, right? Because it sounded like, from what I read about Domeyard, everything was homegrown. You built the servers, you developed the software, you then had to negotiate rack space at the exchanges. That's shoe-leather work, right? You've got to go to the exchanges; you've got to negotiate shelf space. I don't know if it's like department stores or food stores where you're trying to get prime position in the rack, I don't know if it's that kind of thing, where you have to compete against other places. But that's got to cost money and time.

Christina Qi: Yeah, exactly. It's almost like an investment you have to make early on. It's almost like playing a game of 3D chess, 4D chess, something like that.

To give you a sense: we saw early on that a lot of companies before us, a lot of the predecessors in the data space, would just buy things off the shelf, they would use AWS, for example. And we saw that that was their biggest monthly bill. They'd just pay AWS a million dollars every month. That's not efficient.

So, we said, let's build our own virtual private cloud. Let's do it ourselves. Let's build our own cloud instead. And we'd spend a lot of time doing it. At first, it just seems super slow and inefficient, why are we doing this? It's really expensive. Capital expenditure is super high. Our gross margins were awful, negative gross margin. And then over the years, as we're doing this, suddenly it scales really well. And now we're profitable as a result, because we don't have to pay some third-party millions of dollars. So, it's worth the investment, but you have to build the company with scalability in mind early on.

The buy-versus-build question is always tough, but you have to think about the ROI a few years down the road. The difficult part, I will say, is that because building stuff takes so long and is super expensive, one: you probably have to raise venture capital. Two: for us, it took years and years to get to launch, and three years is a lifetime in the venture capital space. It's very easy for anyone to lose patience in someone, unless you set expectations really well. And it's understandable why someone would lose patience, because that's a very long time.

A lot of companies, VCs, investors, anyone, is used to seeing an AI company. You look at the AI industry and you see an AI company—and maybe this is why I hate AI—they literally incorporate today, and by November they have like $100 million ARR. And the question I would ask is: can they maintain it, though? That's another question.

Christopher Reichert: Yeah. I guess it was about a year and a half from your Series A, $27 million, to your public launch, from end of '21 to early '23. So that was the patience.

How did you build the confidence in yourself, and then gain the trust of your investors, to buy into what is a complex vision and a complex path, even early on in Domeyard, I think, but now with Databento? Admittedly with a good history to point back at with Domeyard. But how did you keep them on board for that kind of journey?

Christina Qi: To be honest, it was really tough. As much as you say, "Hey, trust me, bro", I don't think that really goes. You can say that once. Most founders get one shot at that kind of vibe, and it's called a bridge round. You get to raise one so-called bridge round, and those investors will trust you once. And then that's about it.

So, we raised a bridge round between our Series A and Series B. And that bridge round, I think we raised with almost negative runway. What I mean by negative runway is: if we didn't get money in the bank by the end of that week, I'm pretty sure we wouldn't have been able to run payroll. And then what would I tell my employees? "Hey, sorry, we can't pay you guys." And the funny thing is, behind the scenes, I'm protecting the team. I don't want to let people know how dire it is.

Christopher Reichert: You're having sleepless nights but hoping they don't.

Christina Qi: Exactly. Because we don't want people to freak out that much. You want people to, I'm like, "Hey, I've got it covered. I want to do my job and make sure that everyone else will be fed and everyone will be okay. Don't worry about it. I'm raising funding. I got this."

And thankfully, at the last second, we got it. We've also had, I remember we had some investors who literally signed and then didn't wire. And I'm like, you signed a legally binding document. And this wasn't even a term sheet; they signed the financing. And then they're like, "No, we're not going to wire", after signing. We already did the SEC filing and they still wouldn't wire. We've had that happen. So yeah, you can tell I've gained a lot of scars from these experiences as well.

You get that one Hail Mary shot like that, and then you keep going and keep going. And thankfully, I think for us, we were very lucky in the sense that we're just building in an awesome space. We're building in a space where, I mentioned, we're not AI, and I think we're actually lucky because of that. There's just not a lot of competition in our industry.

And how we know that is, sometimes customers will be like, "You guys are too expensive." And we'll be like, okay, that's fine. And a month later they'll come back to us. That's how you know there's literally no one else they can go to. It's hard to notice until you actually start to integrate a data provider. The difference is that it's not that we have one dataset that's more valuable than another, it's that our data is harmonized across all the datasets. It's like a library where all the books are in one language. And then you're like, oh, I see.

Christopher Reichert: So that's the work that you have done and continue to do, take that pain point, which is not-normalized data from all these messy sources, and put it into some orderly fashion that it can be used efficiently, bite-sized by the user.

Christina Qi: Exactly, in consumable quantities. We make it super easy to consume. You can download the data through a regular internet connection. You don't even need to set up dedicated connectivity, depending on how little data you're using. So, it's super flexible.

And everything's also harmonized, in the sense that all the timestamps will match up. It's exactly like you mentioned, it's all in the same language. It's a single API. So, you're not trying to figure out, "Okay, which dataset's the true dataset?" We explain in the documentation how everything's normalized.

Christopher Reichert: So, you were an undergraduate at MIT when you started, how did you wander down towards Sloan?

Christina Qi: Oh, interesting. I think I just kind of fell into it a little bit. I remember at the time I didn't know what I wanted to major in, and then someone said, "Oh, you should do finance." And I was like, okay.

Christopher Reichert: Because your interest in high school, you had a really good biology teacher, right?

Christina Qi: Yeah, I was into bio, but I did not want to do pre-med whatsoever. So, they were like, "Oh, you should do business stuff." And I was like, okay, I like talking to people enough that, you know, finance.

Thankfully I chose the right major. There are lots of great internships in finance and there's an awesome career path. And the feedback loop in trading is very, I like that. The feedback loop is super-fast. Like I mentioned, being able to see how good or bad you do at the end of the day, that's a great feeling, knowing how skilled or unskilled you are. I like an industry like that, where it's based less on luck and more on skill. So, I'm glad that I fell into that industry early on.

And I'm glad that MIT does offer that major for undergrads. It's very rare, I think, for a university to do so, and for Sloan to even offer classes like that for undergrads. I'm grateful I was able to take Bob Merton's class as an undergrad. I feel so lucky to even lottery into a class like that as an undergrad. And who else was there, I took Paul Mende's class, and a bunch of other courses where I felt super grateful to just learn from these amazing people who have taught me so much. And the funny thing is, I still reiterate some of the lessons they taught, even in my Databento days. I still remember some of their lessons and teach them even to my own colleagues.

Christopher Reichert: Not many undergraduates, so soon after graduation in particular, are elected to the MIT Corporation. And then you served, what, seven years on that? Tell me about that.

Christina Qi: Definitely also grateful for that experience. Being able to help MIT, I guess ever since graduating I've always tried to be involved in one way, shape or form with the university. And part of it, first, was just because I lived in Boston. I just wanted something to do. I wanted to be involved.

So being part of the Boston Alumni Association for Sloan, the SBAA, amazing experience. Back then it was hosting the entrepreneurship events. And we did Founders Therapy. I did it with Pat together. That was super fun.

Christopher Reichert: Pat Hubbell?

Christina Qi: Yeah, yeah, yeah.

Christopher Reichert: Oh yeah, she's still on the board.

Christina Qi: Oh, I miss her. So, we would do Founders Therapy together. And for those of you who are unfamiliar, that was an event where we'd be in a classroom, usually in Sloan. We'd move the tables around into a circle, and then we'd just open up about our biggest problems, if anyone's having an emergency or going through some issues, or just have a topic, like fundraising or sales or hiring or something.

Lots of tears were shed in Founders Therapy. And of course we had rules, like whatever happens stays in the room, because some of the information is very sensitive. Maybe some people were being fired by their board, or had issues with their co-founders, or issues with employees. Some of the issues were very sensitive, "Oh, they're being sued by a customer," you know?

But it was really nice to just have a community of people who have been there, who've done that, and you feel like you're not alone. That was super nice. And that's why I've always been involved with MIT, or with any university, any community in general, because just feeling like you're not alone, I think, makes a huge, huge difference. And if I can give one piece of advice, it's to find a community of people wherever you go, because it helps so much.

Christopher Reichert: Yeah, get out of your head, get out of the daily grind of what you're doing. It gives you some perspective.

You've done board work with Invest in Girls, and you have a long-standing commitment to financial literacy for underserved populations. And you're working in a male-dominated profession. Does it feel that way with what you're doing? You look at, like, Wall Street, the movie, for example, and all kinds of other movies, The Wolf of Wall Street, all these names, which have that awful testosterone-driven dynamic. But you're in Utah, and the company's more of a technology thing. Do you still feel that vibe?

Christina Qi: I work remote, so it's one of those things where you're a fish in water, you kind of don't notice it. Maybe on rare occasion, if I go to some conference, I might notice it. But honestly, you just get so used to it that you don't really notice it much.

And honestly, our customers are so nice to us. The funny thing is, people ask me to compare our hedge fund days to my data company days. At the hedge fund, because we competed against all of these quantitative trading firms, they were a lot more competitive against us. At career fairs, I remember, they would kind of run away from us a little bit. And today they come up to us and they're like, "Oh my gosh, we love you guys, your data is the best", because we're helping them now as a data vendor.

We thought they would be rude to us, because I thought people would be rude to vendors, but actually they're so nice to us and grateful for what we're building. So, it's the opposite. I feel like we're actually being treated really nicely by the industry, so I don't notice it as much.

Maybe it's also because I'm getting a little older as well. I don't notice how we're being treated as much as maybe when I was younger and a little more insecure, or whatever it was, and I had more imposter syndrome. Now I don't really notice it nearly as much as I used to.

Christopher Reichert: And maybe that's a function of being around, well, I guess your family, who's known you from day one.

Christina Qi: It helps, though. Just having, I think that's the benefit of working from home. And I tell that to all of my colleagues as well. The privilege of working from home is that you can go pick up the kids from school. You can go to the gym. I don't mind if people go to the gym in the middle of the day to avoid rush hour but just tell us what you're doing. Over-communicate. Don't be that person where we wonder where the heck you are.

The privilege of remote work, even for me, is that I get to live in Utah and have a community here that's far away from the grind, the hedonic treadmill grind that I used to experience a lot more when you're around very high-achieving people. I'm grateful that I can be away from that.

And another piece of advice I have: I have another group of friends beyond the Founders Therapy friends, I do have a group like that in Utah now, but another group of friends I have are close friends here who don't know what a cap table is. I have a group of friends who have no idea what startups do. And I'm grateful for that too, because they're normal. We're friends because of my hobbies.

Christopher Reichert: "Hey, that's Christina, who I ski with."

Christina Qi: Exactly. My ski friends, my jigsaw friends, they would have no clue if I talked about AI. They'd be like, "No, please get that out of here."

Christopher Reichert: You seem more mature than your age. What do you think has given you that kind of perspective? I don't know if you're introverted or extroverted, or if it's something that came from your upbringing or from observing, maybe with the restaurants, I guess, you talked about your parents working in restaurants or whatnot.

Christina Qi: I don't know, actually. I guess it's probably just from experience, to be honest. I've been a founder my entire career, starting from when I was in my dorm room in 2012 until now. So, I've always been a founder. And I've always faced headwinds as well.

Meaning, when Flash Boys came out in 2014, high-frequency trading was in the limelight, but in a negative way. So, I've had to defend not only what we do, but the entire industry. Every time I go on stage, people would basically throw tomatoes at you, figuratively, and be like, "You suck." Since 2014, I've had to be in this defense mode.

And then, funny enough, now I run a data company. And there's this whole negativity around data centers, right? So, people are now, again, theoretically throwing tomatoes at me. And I'm like, dude, I'm not the AI company buying out data center space.

Hilariously enough, by the way, we have another struggle: for many years we've planned a disaster recovery site here in Utah, data-center-wise, because our main data center is out in Boston. We were looking for space earlier this year, and suddenly they were like, "Oh no, all the data center space is gone." And I was like, dang it. So, we literally had to look out of state, and we had to go north, and we had to go to Portland.

I don't know if you can tell, from the perspective of a startup, to be scapegoated around this whole data stuff, I hate it. I feel like a victim as much as anyone. And I get it. I'm okay with flying out somewhere far away and having as little of a footprint as possible.

Christopher Reichert: If you had a chance to have a do-over at MIT or Sloan, what do you think it would be, and why?

Christina Qi: The biggest thing I would do more of is just spend more time with my peers, with my friends. And I hate to say, "Oh, less time studying", but it's kind of true. Because if I think about my favorite moments at MIT, they were the times when I was walking across the Charles River, or eating lunch, or going to Toscanini's, or going to Flour, just the moments that were not in the classroom.

And the funny thing is, like I mentioned, I took Bob Merton's class, I got a C-minus in his class. C's get degrees, guys. I just remember the best moments I had were with my peers, and people who I still talk to today, by the way.

The funny thing is, in May we held an event in Shanghai, in China, and we needed speakers on a panel for a big data event. I think we had like 300 people register. And at least two of the panelists were MIT Sloan, which is so funny. We overlapped at Sloan and we knew each other. If we hadn't met each other back then, this event wouldn't have been possible.

And the other funny thing is that these people are some of the most successful people in our industry. I'm not going to dox them too much, because that's their success, but they're some of the top portfolio managers not only in all of China but in all of the world. I can't even tell you how, the amount of success they've seen is insane, absolutely insane. And it just makes me so proud to see that, and to be like, I was a part of that. I knew them when they were students. I knew them when they had nothing. And to see their careers grow like that is absolutely enormous.

I just wish I had connected with more people. I wish I had gotten to know more of my classmates like that. So that's why, okay, if I had to redo it, I would just want to spend more time hanging out with people. More study breaks. Let's just do all the study breaks. Why am I studying? Just do the breaks, instead of the studying.

Christopher Reichert: You’ve had a lot of success in your life, with Domeyard and now Databento, I'm not saying it's been easy, I'm saying it's been, I mean, we can all look and say that Christina Qi is a successful businesswoman. What is your definition of success?

Christina Qi: For me, success is the number of hours you can play video games during the day. That's actually how my friend defined it back in college, and that's always stuck with me.

It's not video games necessarily, what the meaning of it is, is that success is the number of hours you can spend, or afford, to do the thing you truly want to do during the day without consequences. So, if success for you is taking care of your family, if it's for you just relaxing at home and watching Netflix, or if it's traveling the world and being carefree, but without consequences. That's success.

For my friends and I during undergrad, I remember that was video games at the time. So, my friend would say, "Success is the number of hours you can play video games during the day." And I was like, that's so true. And that always stuck with me as the definition of success.

Even though nowadays I do play video games, I rarely do. And do I find enjoyment, sometimes I find more enjoyment from jigsaw puzzles. But I still say it as video games, just because I think that has the most ring to it, and I think it's the most hilarious and funny. But I think that to me is still the best definition.

It's just the number of hours you can afford to do what you truly want to do. And that doesn't mean you have the most money. It doesn't mean you have the most, not even the most happiness. It's just whatever you want to do, without facing consequences of your actions later on.

Christopher Reichert: That's great. Well, I want to thank Christina Qi, a 2013 MIT graduate with a Bachelor of Science in Management Science, CEO of Databento, for joining us on this episode of Sloanies Talking with Sloanies.

Christina Qi: Thank you, Chris.

Christopher Reichert: And if you want to follow her work, I would say start at christinaqi.com. And of course, if you want high-quality, on-demand market data, look no further than databento.com, a growing company.

So, if you have any ideas for further guests or topics you'd like me to explore on Sloanies Talking with Sloanies, drop me a line at crf@sloan.mit.edu, or at the podcast inbox, sloanalumni@mit.edu.

Sloanies Talking with Sloanies is produced by the Office of External Relations at MIT Sloan School of Management. You can subscribe to this podcast by visiting our website, mitsloan.mit.edu/alumni, or wherever you find your favorite podcasts. Support for this podcast comes in part from the MIT Sloan Annual Fund, which provides essential flexible funding to ensure that our community can pursue excellence. Make your gift today by visiting giving.mit.edu/sloan.