The New Quant Times

Welcome to The New Quant Times. This month, we chat with world traveler Nathan Landman, an MIT alumnus, ex-ML engineer, and ex-quant researcher who has worked at Apple, Capula, and BFAM Partners. Today, he's based in Hong Kong and experimenting with his own startup ideas - his most recent project being Try It On.

Let's start from the beginning. You went to MIT, right? How did you first get into the quant field?

I had an interest in finance when I arrived at university. Since I studied computer science, the only companies recruiting from our department were quant firms. Most had huge booths at the career fairs and would take you to dinner, treat you well. So it was natural for me to go to these events and meet people. The people were interesting, so it became a kind of soft networking. MIT was probably a target school for quants, so I fell into it. I did two internships in finance, then two in software, and after graduation I went the finance route.

Was finance something you'd always been interested in before college, or was it just the opportunity being there and you thought, "Okay, I'll give this a shot"?

It was definitely the best opportunity. I was more interested in bio research when I first got to university. But most of my friends were doing computer science, and I felt left out, so I started studying it too. I ended up doing a master's concentration in machine learning. Honestly, I would have been better prepared for quant with more math courses. I wasn't specifically aiming for quant, I just fell into it.

That's interesting you mentioned math, because most people I've talked to have a competitive math background. For you, without that heavy math foundation, how did you handle the transition?

I definitely felt like an outlier. Most of my team were math PhDs, or in electrical engineering or physics. But I became an asset in a different way. My colleagues would have ideas or theories and need time to code them up, but I could do that really easily. So I played to my strengths. Getting the job was tougher, I had to train hard with brainteasers and interview prep. For my math friends, it came more naturally. That was a disadvantage. But once inside, the computer science background was very complementary to their skills.

So, the interview process for quant roles is notoriously difficult. It’s also arguably not necessarily reflective of what you actually do on the job. Any thoughts on this?

That's true. But interestingly, most lunchtime and in-between-work conversations were about those kinds of problems. A lot of my math PhD colleagues would grab a whiteboard and solve problems just for fun. I'd sit back and watch (I didn't have the rigorous proof background).

Math all day, every day. That's funny. So looking at your background, you had a pretty interesting geographical journey: internships, full-time roles, all around the world. Could you walk me through how that path came about?

I grew up in South America, went to school in the States, and my first internship came from a finance career fair. Someone told me, "This is your only time to go have fun, don't take freshman internships too seriously." So I went to India my first year. It wasn't professionally enriching, but it was a lot of fun. MIT has a great international internship program, so I leaned into that.

For my last internship, I joined a software engineering company from the career fair. They had an office in Cupertino, but I'd just spent a winter at Apple and didn't enjoy Cupertino, it was boring even though the job was good. So I asked if they had another office. They said, "Well, we have one in China." I said, "Hell yeah, let's go to China." So I worked in Guangdong. Then someone from Hong Kong reached out on LinkedIn about a quant role, and that's how I ended up working in finance there.

That's awesome. I always wanted to work abroad. I studied abroad, but never worked. It was always a dream of mine.

It's really fun. If you're at a big company, most have offices around the world, so they can send you abroad. That's one of the perks.

Across all these different places—China, Hong Kong, India—and working in software engineering versus quant, what differences did you notice in the people and work culture?

Cultural dynamics vary a lot. In Hong Kong, half the office was mainland Chinese, a few were local Hong Kongers, and the rest Westerners. Westerners tended to be more outspoken, while the mainland Chinese were quieter in meetings but extremely punctual, always arriving before the boss, leaving after. But at the end of the day, performance mattered most. Our firm didn't care when you came or left as long as results were good. Eventually, even the mainland hires adapted to that culture. It was very top-down, our boss was American, so he set the tone.

Were you able to speak the local languages, or was everything conducted in English?

Mostly English. I took Mandarin classes but not enough for a professional environment.

Seems like it worked out fine anyway.

Yeah, it was good.

Going from quant to what you're doing now with startups, how did that shift happen?

In quant, depending on the company and culture, work can feel siloed. You might spend weeks just collecting data, cleaning it, and running backtests. You don't need to watch markets daily if your strategy tests well historically. I felt a bit secluded from the real world.

I tried trading for a bit, but I realized I'm more social. I wanted to build something people actually use, get feedback, and improve it. I'd always been interested in startups. During COVID, between jobs, I started tinkering with AI projects. One took off, so I postponed a sabbatical for two years. Now I don't know if I'll go back to finance. I do miss it, not the quant research so much, but more the front office work. We'll see if an opportunity comes up.

So you're playing it by ear.

Exactly. Startups are fun too, you get new problems every day.

Just to clarify, when you were in finance, you were doing quant research specifically?

Yes, two years in quant research, then a year with a portfolio manager on the sales side.

Got it. So you've experienced startups, finance, and software engineering. For very technical, intelligent people today who aren't sure what career path to pursue, would you recommend going into quant or starting a company?

It depends. I ask myself: on a free weekend with just your computer, what do you naturally gravitate toward? These days it's easier than ever to set up a small crypto trading system. Put in $10 or $50, test strategies, run simulations. If you feel drawn to go deeper and deeper, quant might be for you. If instead you'd rather spend your time exploring the latest AI tools or something else, maybe startups fit better.

Interviewers can tell if you genuinely love quant or just want the paycheck. If you're not into it, it's much harder to break in.

Basically try things out, see what naturally fits, and go from there.

Exactly. I interviewed plenty of fresh grads. I'd ask, "What do you know about quant?" They'd say, "Oh yeah, we trade finance." I'd ask if they'd done anything on weekends. Most said no, or they'd followed a tutorial once a year ago. That's an immediate no from me. Straight A's don't matter if you have no genuine interest.

Now, there's an exception: math majors. The problems they like to solve are very similar to those in finance, so it's easy for a hiring manager to say, "Your math problems translate well here, you'll likely enjoy this."

Finally, what advice would you give to college students who are aiming for similar roles?

I'd tell people not to load up on all the hardest classes just for the sake of it. Instead, spend more time on side projects that genuinely interest you. The key is doing those projects either with mentorship from professors or with your friends, ideally both.

What really makes you stand out is being able to talk passionately about something you built on your own time. Those side projects show real curiosity and initiative.

Great stuff!

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Welcome to The New Quant Times. This month, we chat with Guang Cui, an MIT graduate and ex-quant trader who has worked at Five Rings, Jane Street, and Akuna Capital. Today, he's the CTO and co-founder of Miyagi Labs, building an AI tool that transforms Youtube videos into personalized courses..

Q:

So, let's start with a brief introduction, who you are, what you do, and we can go from there.

Guang:

Yeah, sure, cool. Well, I'm Guang. I'm from Maryland. I went to school at MIT, studied computer science, and I guess I got thrown into the quant world when I was in college. Then, I did a couple of internships and worked fulltime for a little over a year, and now I've started my own company with a college friend who also has a finance background. We've been running it for about six months.

Q:

Nice, cool.

What was the path you took to get into quant? Was it like a spur of the moment thing, or was it something you had your mind on for a long time?

Guang:

I would say maybe it's a little different these days, but at the time, I didn't think it was that popular going into college, so I think people didn't really know about it, but I did math and computer science back when I was in high school. I really enjoyed that, and I think once I got into college, there were career fairs and, at the time, that's when people started to talk about it. I think quant firms, especially these days, are pretty aggressive in recruiting. So yeah, I sort of started interviewing. Some of my friends were doing it, and I figured I'd check it out, see how it was. And yeah, I guess that's how I got into it.

Q:

Kind of just how things lined up for you. I guess.

Guang:

Yeah. I'd say so.

So were you into math competitions and stuff, back in high school?

Yeah, mostly early part of high school, but also, I guess later too, I was a math team captain. I would say I was definitely in that world, which certainly helps for the quant interviews.

You said you enjoyed some parts of the job. Would you say, on a day to day basis, you felt pretty challenged and happy with what you were doing?

Yeah, I would say so. I think it certainly comes with every job, and there are pros and cons to it. I think the things that I enjoyed were, like, the game aspect of it. I think a lot of firms will make you play games and teach you how to play poker because it's sort of similar to some aspects of trading. I really liked when we did mock trading or played some of these games. And it was a bit of a mini-game where you could try to get better. It was pretty competitive, and you could see how well you were doing. Those are some of the things I liked about it. I enjoyed mentoring the interns. Then at a certain point, it became a little bit repetitive. For me, startups seemed more interesting. There are more opportunities to have a greater impact, in my opinion. So that's why I sort of switched over recently.

Was entrepreneurship something you had always wanted to do, or was that also a spur of the moment thing?

Hmm. I would say I had more of an idea for entrepreneurship earlier on than for quant. I think growing up, I wasn't entirely sure what I was going to do, but being an entrepreneur was certainly up there. So this has definitely been in the works longer than being a quant trader, for me.

How does your day-to-day now compare to when you did work in quant?

Very, very different. As a quant trader, things were hard, but once you learn the ropes, your day-to-day is mostly the same. You'll spend hours trading. You'll also be looking at the markets and thinking, "Okay, here's where I can potentially see some sort of signal, and I'll incorporate that into my next day." And of course, there are other research projects you can do, but overall, it's very confined to one thing. Now, as a startup founder, it's a very, very different day-to-day, and we're just in the early stages. I'm sure it's going to be a lot different a few years down the line, but as of right now, we have to code a lot. The coding is quite different. It's also a lot more calling people, doing sales, and a bunch of random one-off things as well. Now it's like almost all of my days are consumed by the startup, which is great because I think I'm way more invested. At the end of the day, my quant job was sort of a nine-to-five, nine-to-six job, whereas now it's, you know, a bigger part of my identity these days.

So wake up, start up, and then… more startup stuff and go to bed. Startup, that's you.

Exactly, yeah. I mean, I do have time to take breaks, socialize, have fun and stuff. But a lot of it is startup related.

Was there a notable inflection point for you where you're in quant and the next moment you're like "this is the right time to do my startup"?

Certainly a few. In quant, there's this whole payment cycle thing where you get your bonus at the end of every year or so, as well as signing bonuses. Because of that, there's an "ideal" time to leave, which is right after you've received your bonus. I've talked with friends who are in quant or other roles as well, and there's always a time when you could leave. So I was pretty sure I wanted to leave after I got this bonus. But on a deeper level, I realized that another year in quant would probably feel a lot like the one I'd just finished. The learning curve had started to level off, and that's usually a good sign it might be time to try something new. And I think that's also a pretty good sign to think about trying something new because—I don't know—I'm pretty young, and I don't want to be trapped in a job where I'm just doing the same thing over and over again. So I think when I was coming up on that year mark, I realized it might be fun to do something different.

Sort of premeditated, a little bit.

I would say, so, yeah.

Was there any overlap between what you did in quant and the idea behind Miyagi Labs? Where did this idea of transcribing YouTube videos into courses come from?

That's a good question. Well, the big reason behind what we're doing now is because both my co-founder and I used YouTube videos a lot when we were young to learn different things, whether it be math, chess, or even certain sports. YouTube is a very valuable resource, but it's also a huge platform that's not just educational. So we wanted to bring the educational side of that out, plus integrate AI into it. AI is quite good at helping you get better and understand different concepts. So that was a big part of it. I think with quant, I'm sure it's helped subconsciously to some extent, but I wouldn't say it was a huge part of why we started the company. It's funny, because my friend and I both did finance, but I wouldn't say finance is a huge part of what we do these days. Some of the skills have definitely carried over in some sense.

What you said about AI being good at helping people learn—I've had AI help me make a study guide for this topic, and then I'm like, okay, yeah, wow, pretty good.

Right? Exactly. What we're trying to do is streamline that. We want to make the user experience better so that you would come to our site if you wanted to learn anything, as opposed to just going straight to ChatGPT.

You've had experience at a few of the bigger firms, like Jane Street, Akuna, and Five Rings. Across all of those, were there any similar qualities you saw in the people who work there?

Similar qualities? Yeah, I would say so. The average person who's a trader is definitely on the more competitive side and pretty good with numbers. I'd say those are the big ones: being somewhat competitive and also being intuitive when it comes to numbers. I'd also say maybe being interested in playing games, whether it be poker or strategic board games. I think those are definitely skill sets that help as a quant trader, which is different from a software role or, like, maybe even a research role at some of these firms. Generally, all cool people, though.

The general consensus, or at least what I saw at school, was, people think you have to be a genius to get into quant. You know, gotta be "cracked" or whatever. Do you think, with enough diligence and tenacity, anyone can get in? Or do you really think there is some inherent intelligence that you need?

I think the inherent intelligence part is a bit overrated. It certainly helps in some capacity, but there are a couple of reasons people think that way. One big reason is that the interview process selects people who have done math in high school and such. And I don't know, I personally don't think that the interview process correlates to how well you do during your day-to-day as a quant trader. You could say the same thing for, like, LeetCode, SWE, and internships. I would say what's more important than just having that genius, "cracked" personality or something is being quite interested in quant and actually being passionate about both the industry and the willingness to get better. I've seen a bunch of people who were in college, freshman/sophomore year, who didn't do too much math growing up or things in the quant sphere, but they were able to land the internship and do really well just by staying curious, putting in the effort, and getting a little better every day or every week. In my opinion, that's a much more sustainable path forward.

Some great insight there.

Comparing what you just said to startups, I personally think anyone has the ability to go and make their own company, even more so now, with AI. In your opinion, do you think everyone has this same potential?

Yeah, I mean, similar concept, right? I feel like, generally, people can do more than they might think on average. I'm sure some people are different, but yeah, you'd be surprised by how much you can learn by just making it your full-time job to focus on a certain thing. Whether it's quant-related work or startups, I've learned a lot over the past year just by doing things on the job. That said, startups call for a slightly different skill set. You need a lot of passion and competitiveness to some extent, or at least drive, but there are a lot of other skills that are more interpersonal or more idea-heavy, basically. The startup world is such a big ecosystem, and you have to know a little bit about a lot of things rather than focusing deeply on one very specific problem, which is more typical in quant roles.

That's an interesting point about knowing a little bit about a lot of things, as opposed to really specialized knowledge.

Yeah. And I think, I mean, you probably should be quite good at, like, whatever your startup is as well. If you're doing an education startup, like we are, we're very passionate about teaching and learning. If you do a startup specializing in healthcare, it definitely helps for you to be in the medical space or have someone who's a doctor on your team. It's not like you can just zero in on that one thing; you have to understand how to talk to people and get sales. Yeah, the day-to-day is a lot more diverse than that.

That makes sense. I mean, I guess you're starting your own company, right? You're kind of doing like everything now at this point.

Yeah, exactly. A lot of different hats, as they say.

What's the future plan? Any big things planned that are coming up with your startup, or just things in general?

Yeah, absolutely. So right now, we have a lot of different features on the site. For example, if you're studying with a YouTube video, a PDF, or even a textbook, you can plug that into our site and we'll generate an entire course for you. We're working with a bunch of creators, some with millions of subscribers on YouTube, as well as schools that have a lot of learning resources online. We partner with them to create official courses you can take. Looking ahead, we're building on this foundation by adding more customized plans. For example, if you want to prepare for a specific test, like the SAT, we'll have a great way to do that. We're also creating a customized blackjack or poker learning experience so that, if you want to learn those games, we'll be the best place to do it. And years down the line, our goal is that if you want to learn any new skill or topic, Miyagi Labs will be the first place you go. There's a lot to do, but we're excited for the journey.

So like super personalized Khan Academy, almost an adaptive Khan Academy.

Yes, that's a great way to describe it. We do say that sometimes, like allowing other educators to become their own sort of Khan Academy, but for their niche, and we'd be the platform to host all of that.

Awesome, excited to see where you guys go with this.

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