BTU #168 - Army to Quantitative Analyst & Data Scientist (Ryan Whitt)

On my second tour of duty in Iraq, I started reading a stock investing book. I didn’t know anything about it and I needed to kill time when I was bored. I don’t even remember the book but it was compelling to me because I was learning about a way to make money by not actually owning anything. It was interesting to me that that was feasible.
— Ryan Whitt

Subscribe on: iTunes | Stitcher | Google Play            Enjoy the episode? Review us on iTunes!

Ryan Whitt is a Quantitative Analyst at Arches Asset Management. He started out as a Sergeant in the Army, where he served for over 8 years. He has worked as a Futures & Options Analyst at BP, a Middle Office Trading Analyst at XR Trading, and a Data Scientist at DHF Team. He holds a Master’s in Applied Statistics from the University of Colorado Boulder, and a Bacherlos in Economics from Indiana University Bloomington.

Why Listen: 

In addition to talking about the Quantitative Analyst position and Data Science in general, Ryan and I also talk about two advantages to being in a position where you work market hours. One advantage is that the work week is fairly predictable - for Ryan, he generally works 6:00 am - 2:00 pm MST, rarely having to work on the weekends. Second, every single day Ryan and his team get a "report card" on how they performed - they get immediate feedback from the financial markets on how they are doing. If you love numbers, this is definitely an episode worth listening to.

Our Sponsor: 

  • StoryBox - People trust each other more than advertising. StoryBox provides the tools and supports businesses need to take the best things customers say about them, and use them to drive more sales and referrals. StoryBox offers a 10% discount to companies employing veterans of the US Armed Forces.

  • Audible is offering one FREE audio book to Beyond the Uniform listeners. You can claim this offer here, and see a list of books recommended by my guests at

Selected Resources: 

Transcript & Time Stamps:


Joining me today from Boulder, Colorado is Ryan Whitt. Ryan is a quantitative analyst at Arches Asset Management. He started out as a sergeant in the Army where he spent eight years. After leaving the Army, he worked as a futures analyst for British Petroleum, a middle office analyst at XR Trading, and a data scientist at DHF Team. He also has a Master’s Degree in Applied Statistics from the University of Colorado as well as a Bachelor’s in Economics from the University of Indiana - Bloomington.


What do you do at Arches Asset Management?

In order to understand what I do, it’s necessary to understand what futures market is. It’s very similar to the stock market in which there is an exchange and you an buy and sell contracts. The difference is that with a stock, you’re buying a piece of the company. With a future, you’re buying some sort of underlying commodity. For example if I’m buying a corn future, I’m buying a contract worth 5,000 bushels of corn, and there’s an expiration date on that. So if I purchase that contract and hold the contract to the expiration date, I will then take delivery of the corn at whatever price I paid for the futures contract. But most people don’t hold the contract until delivery. What they want to do is buy the contract when the price is low and sell the contact back when the price goes up.

What Arches Asset Management does is buy these contracts on behalf of large investors. They invest in us because they want exposure to those futures markets but they don’t have the expertise to buy and sell those contracts themselves. So we make those trades on their behalf and then get a cut of the profits.


How would you explain your role as a quantitative analyst?

I write computer programs that analyze market data and try to find patterns in that data that we can then use to help us make trades. I work at a small fund so I do other things as well like risk management. Anyone that works in this industry has to understand that your job isn’t usually limited to the specific role that you are hired for. Usually you'll find yourself working in other departments as well.


What does your day to day look like?

I get into the office at 6AM. Many futures markets are based around Chicago or New York so I need to be in the office when these markets open. During the morning, I also look over the data that my programs are compiling. We check to make sure that we agree with the profits and losses we’ve seen. So I make sure that our automation is working. If everything is working the way it’s supposed to, I move into working on different projects. That could be requests from hedge fund managers, improving trade algorithms, or automating a new process.


What does that mean when you do a market analysis?

A lot of times, they will specify exactly what they are looking for in a particular market in terms of volatility and profitability. A lot of it is a simple statistical analysis. So it can be as simple as that.


How did you learn to write algorithms?

I spend a lot of time in R. A lot of people use Python but most of the time I use R. The way I learned it was through teaching it to myself little by little. In graduate school, you don’t necessarily learn all the tools that you need but you learn what you need to know. So I ended up taking a Coursera class on computer programming and then sought out different opportunities in my daily work to use R and practice automating things.


And what do you find yourself doing in the afternoon?

There’s usually administrative work that I’m doing. I tabulate all of the trading that we do at the end of the day. I calculate an end of day profit and loss. We send that information out to our investors. If it’s an easy day, I usually leave by 2 or 2:30. If it’s a longer day, I’ll work until late afternoon.

I rarely have to work on the weekend. Once in a while I’ll go in if I’m working on a project. In general, it’s a great lifestyle because you’re not working the hours that someone would be at an investment bank.


I think one of the appealing things about what you described is that every day you can analyze what the successes and failures were. There’s a very tight feedback loop in this industry.

That’s true and I will say that you have various types of trading firms. With day trading firms, they only trade during market hours and aren’t exposed to market movement through the night. For us, we look a bit more long term. So you’re right that you get a lot of immediate feedback from the market but sometimes you can take a big one day loss but you’re holding onto something for the long term. So you have to have the stomach for having a bad market day but sticking with it long term in hopes of an eventual profit.


How did you get into this line of work?

On my second tour of duty in Iraq, I started reading a stock investing book. I didn’t know anything about it and I needed to kill time when I was bored. I don’t even remember the book but it was compelling to me because I was learning about a way to make money by not actually owning anything. It was interesting to me that that was feasible. I ended up studying Economics in college. I didn’t know anything about the futures investment but randomly got into it through my job at British Petroleum. I also did a lot of coding there which I enjoyed. So one thing lead to another after that.


How important is an advanced degree to get into this career path?

It depends. One approach you can take is self study. Many of the skills I use in my daily life is not what I learned in graduate school. We live in a world today where there is so much information at your fingertips. But if your preference is to learn at a large firm, it would be difficult to get that position without an advanced degree.

Another cool thing about this industry is that it’s very results driven. If you can go out and create an algorithm, that’s going to be useful to people and you can use that in lieu of an advanced degree.


Do you have any resources that you would recommend?

I took the Coursera Johns Hopkins Data Science certification. I know there a lot of other ones as well. It really got my feet wet with coding R.

There’s a good R programming booking - Introduction to Statistical Learning.

There’s a website called Kaggle that offers various data science competitions. It’s a website in which usually you need to write code to make a predictive analysis. You upload your code and they will rank your code against other people.

There’s also Data Camp and Codecademy - both have R and Python programming tutorials.

If you’re interested specifically in trading, I would recommend the books Market Wizards and Flash Boys. Both will give you an idea of different challenges in this industry. The books Systemic Trading and Algorithmic Trading are also really good.


I love that idea of Kaggle where you can write your own code and then have it ranked against other people.

Yes, any opportunity where you can do any applied project you will learn more than being in a class or reading a book.


What kind of a person would do well in this industry?

Are you analytical? Do you enjoy breaking apart a complex problem? I think it’s a good fit for people with a background in military leadership. Comfort with numbers and coding is also important. The coding component intimidates a lot of people but it doesn't really need to. There’s the initial challenge of learning the program but after that it can be really fun to use coding to solve problems.


Is there anything else that you would like to share with our listeners?

I went straight to school immediately after leaving active duty. This kept some structure in my life. This won’t work for everyone but it worked really well for me. College is a lot of fun. You’re getting paid by the military to go to class and learn. If you don’t know what you want to do, I think it’s a great way to figure that out.

The other thing is that I would encourage people to keep a learning mentality throughout their life. Job markets are changing very rapidly. So stay learning and don’t get complacent.


I love that thought of lifelong learning. I completely agree. Thanks very much for your time today, Ryan.