Carnegie Mellon University

Braxton McKenzie

Braxton McKenzie

Partner and Data Scientist at KCL Capital

When did you first become interested in quantitative finance?

Growing up, I was always interested in numbers. I remember watching numbers reported in the nightly news and trying to figure out how many times our family would have to go to the nearby waterpark in order to make it worth a season pass. In college, I majored in economics to build models that would describe people’s behaviors, and more generally, the world. As I started to take more classes, I realized the benefits of having an applied degree within economics. My dad gave me the book, “The Quants” by Scott Patterson, which brought to life the multiple career paths for people like me – people interested in markets and numbers. I realized that if I wanted to advance in the quantitative field, I would need a graduate degree.

What types of graduate degrees were you considering?

I was only looking at financial engineering programs, and I applied to all of the top-ranked schools. Carnegie Mellon stood out as a leading university with strong job placements. I knew I wanted to be near the activity and live in New York City. The MSCF’s program location, job placements, ranking, and curriculum from four different disciplines – mathematics, statistics, finance and programming – really interested me. I thought its well-rounded curriculum would help me develop more technical skills, especially since I didn’t have a background in programming.

How did you land in your career?

After graduating from MSCF, I wasn’t sure what area of quantitative finance I wanted to pursue. During the recruiting phase, I applied to everything and was contacted by Tony Berkman from Majestic Research, who was a graduate of the MSCF program. He was interested in having me join their investment research team. This gave me the opportunity to work with big data back in 2011, which at the time, was a new area. The idea of working in a new, cutting edge field was really interesting. I worked on a healthcare team and built all of their models and programs that could do approximately 75% of a day’s work in just two hours. After interning there, they made me a return offer to be in their research and development group where I would work with raw data of the big data sets, doing analyses on what data sources to purchase, building out coverage, etc. I eventually built a modeling process that could estimate all of the internal research, which showed me how much of an impact I could have on the markets based on the modeling that I had already done. I discovered there was a lot of demand for my skills and thought that I could take what I had learned and apply it to the active markets, which made me want to move to the buy side.

Can you please describe your average day?

I don’t have an average day; it’s more project based. My process generates internal reports looking at different investment factors, descriptive statistics on screens, different stocks, etc. It’s a process that I built, and we focus more on one-off projects. For example, we track video game stocks. An important metric for these stocks is the number of players currently playing games. When we have a new release, we can see the increase in player base, which adds to the mosaic on how to invest. It gives us more confidence to short stock, and because we’re still fundraising, investors ask for patterns of historical trading. We create analysis for potential investors, which is why our strategy is different from others.

Where does your entrepreneurial spirit come from?

For me, it was a good next step in my career. I was in a big institution with access to all of the resources, but there was a lot of overhead. I was in a high risk, high reward industry, and if I wanted to take a shot at being more successful, I had to step out and take a risk. I had a startup fund and had the ability to shape and structure the business how I wanted it. It’s a more profitable model, and I enjoy building internal tools that are critical to the investment process.

Will you always stay in this role?

I found something that I’m good at and that I enjoy. I enjoy following the market, and I found a career where my entire job is to discover and analyze data. I get to use my economics and follow the timeliest trends in technology. I get to do what I enjoy on a daily basis, and I’m intrigued by where the world is taking us. My curiosity and passion for technology and AI is stimulated through my job.

What skillsets are required in order to be successful in this field?

You need to pay close attention to detail. So many times, when working with math and data, you can dismiss an outlier as an anomaly. However, there could be a fundamental shift in the data you’re analyzing, and you can’t miss it. You also have to be driven and self motivated. In the investment management field, you eat what you kill. If you’re not performing, you’re not going to get paid. Every day is an opportunity to improve the performance of the firm and the general investing process.

How do you feel about this career path?

It’s a great field. The financial industry as a whole is always evolving because markets are always evolving. From my seat, I’ve had the opportunity to see different cloud technologies implemented in the workplace. You get to see different natural language processing techniques; get to be at the forefront of these technological implementations; and get to see how the economy is doing. There are so many areas to go into depending on what you’re passionate about, and it’s all incredibly rewarding.

Do you have advice to anyone pursuing a job in this field?

One of the most important parts of an interview is showing you’re passionate about something. As an employer, I’m looking for someone who has built their own model, built their own AI, or is taking initiative on their own without guidance. Maybe it’s a side hobby they’re working on, but in general, when you’re applying to a job, you should show something you’re doing outside of just schoolwork. We get hundreds of resumes from really smart people, and you need to show something that will set you apart – something that will make you stand out vs. someone who just earned good grades.

Anything else?

Make sure you’re passionate about markets. It’s an extremely demanding job. If you’re doing it just as a job to get paid, you’re going to have to want to get to work every day and hustle. News will affect your company on a daily basis. If you’re just trying to put in the hours, you’ll burn out quickly.

Were there MSCF classes that you found to be helpful throughout your career?

The time series classes were really helpful. They provided a better understanding of proper techniques and time series data, which is what I work with on a daily basis. Knowing the minute-by-minute stock level data and being able to use that has been instrumental. The general programming classes were also helpful in teaching me how to think more like a programmer, how to structure code and how to write it. The course taught standard procedures that will help save time in the future. The finance classes provided an overview of different assets and an understanding of how futures work.

Who will be the most successful in the MSCF program?

It would be helpful to have a background in programming. Out of all of the classes, if you don’t have experience in programming, you could fall behind. The classes later in the program require that you have a solid coding base, and you can get hung up on implementation vs. learning the material. You should also have a passion for the markets and an idea of what you would want to invest in. If you don’t have that passion, you may burn out, and if you’re not sure, it could be difficult.

Which MSCF services or resources did you find to be the most helpful?

The MSCF Career Center was really helpful – especially the mock interviews and resume preparation. Going into the program, I never had a big multibillion-dollar company interview that required me to be that polished. The staff in the career center would record interviews and allow us to go back and analyze them to better understand the importance of wording and how we presented ourselves. The staff helped us learn how to differentiate ourselves from hundreds of other candidates.

Did anything surprise you?

I was surprised by the difficulty of the program. I never earned less than an A in any class in high school and during my time in undergrad, and suddenly, I was with some of the smartest people in the world. It was an awakening. As a student in the MSCF program, you really have to understand the material and not just do the homework.