Testimonials

…within the field of Computer Vision, but I’ve also spent a good bit of time thinking about everything from RLWE homomorphic encryption to AI operationalization.

Why did you choose Georgetown?

I was an undergraduate mathematics major at Georgetown University. Upon graduation, I realized (very quickly) that if I was serious about practicing mathematics as a professional career, I would need at least a master’s degree (or many years of experience). The masters seemed like a quicker path to career happiness, and I had ties to the Georgetown community. 

During undergrad, I had taken an advanced linear algebra class with Professor Ken Shaw. I went to see him three months after I graduated with my undergraduate degree to express my discontent working as an analyst at a fintech startup, which I’d very quickly realized was certainly not the direction I wanted to take my career. I knew, at that point, that as part of my professional life, I wanted to develop new mathematics and work closer to the cutting edge of AI/ML. However, I was lacking some of the necessary programming and applied mathematics skill sets – particularly around deep learning frameworks, modeling, and paper-reading/writing. Professor Shaw told me that participating in the MAST program would help me get closer to my goals, and I trusted him, both as a mentor and a friend. So, I only applied to Georgetown MAST, was accepted, and will forever be grateful to Professor Ken Shaw for helping me begin my professional career.

How did the MAST program prepare you for your career?

The program taught me the programming, applied mathematics, research, and theoretical backing necessary to successfully enter the workforce and meaningfully contribute towards my team’s research objectives. Most of my professors were also working professionals with excellent advice and years of experience in the field. Every class I took during my masters either provided a great deal of personal edification or professional wisdom.

What’s your advice for alums?

Your masters degree is only the beginning. Continue to both grow your deep understanding of mathematics/programming post-masters and your personal network – both will help you have a successful, fulfilling career (of which I am still only just starting). 

Also, a lot of AI/ML modeling relies upon underlying hardware, sometimes a vacation does result in better model performance.

…and as a legislative assistant in the House of Representatives, both part-time and concurrently for several months. I was then a statistician at the Science and Technology Policy Institute for two years. I left to be Director of Data Science at Impact Research, a small firm doing data science for auto safety. After two years there, I left for In-Q-Tel, a nonprofit at the nexus of venture capital, startup technology, and national security, where I stayed for 6 years. I left in 2023 to start a business, Foundation, whose mission is to help organizations make faster decisions with less uncertainty by measuring narratives that drive economic outcomes. In 2023 I also completed my PhD in Computational Science and Informatics at George Mason University.

Why did you choose Georgetown?

Truly, it was circumstance. (But I am so happy I did it!) I had been a math minor as an undergrad and was hoping to go into a PhD program in economics. Rather than taking more undergraduate math classes, I discovered that MAST would let me get a master’s degree. Its flexibility and not requiring a thesis were perfect for my goals at the time, even though my plans changed.

How did the MAST program prepare you for your career?

I cannot overstate how valuable a rigorous education in probability and statistics has been for me. In today’s world, so many people are getting into machine learning and data science, and you need a way to differentiate yourself and add value that others can’t. Yes, you need to know how to program. But that isn’t a differentiator. Most people simply don’t have the background to engage with the broad swath of methods in use today. But my education allowed me to engage with all areas of machine learning and link them back to more basic principles. That gets me unstuck, finds creative solutions, and gets to deep issues faster than many others coming from different disciplines. Frankly, MAST’s probability and statistics curriculum is so rigorous, I’ve found that I know more theory than many graduates of other masters-level statistics programs.

What’s your advice for alums?

Your education will leave you well-prepared for the technical aspects of a beginning career in data science. Lean into learning soft human skills like empathy and communication, and you will be extremely well-placed for the remainder of your career.

…and Spanish, and then I spent several years abroad working in economic development (as a Peace Corps Volunteer in Ecuador, a Fulbright Scholar in Portugal, a Boren Fellow in Turkey, and as a J-PAL research associate in Mozambique). I had previously completed an MPA and MA in Economics, so I had done my calculus and linear algebra sequence and some econometrics courses, but that was it. I wanted to pursue more rigorous quantitative tools while simultaneously working full-time.

It took me three years to complete the degree part-time, and it was intense, but it paid off. After just one year in the program, people at my organization (the Inter-American Development Bank, or IDB) heard about my background through the grapevine. I was promoted as a data scientist for a vice presidency at the IDB, where I worked on several awesome projects using predictive modeling and network analysis. Outside the IDB, I also led several courses on machine learning and coding in R, and I was twice a speaker at the R|Gov conference.

Now I’m a Ph.D. student in statistics at Carnegie Mellon University, which is an ideal setting for combining statistical theory with useful applications in machine learning, industry, and public policy. I am so honored to be a Georgetown alum and thanks to my professors and the MAST team, I am living my dream.

Why did you choose Georgetown?

One, Georgetown’s MS-math/stats program is the perfect blend of theory and application. As its name suggests, the program is based on math. I always recommend math as the “starting point” for careers in data science or statistics: it’s a common foundation so we can communicate ideas precisely and in a common language. I learned to code in R mostly by doing, and I became fluent in visual tools such as Tableau at work. I have a relatively weaker background in computer science, although many of the tools are the same (such as numerical methods).

Two, I was looking for a program that would fit my full-time work schedule, and the evening class hours were perfect for me.

Three, Georgetown has an excellent overall academic reputation, and the department and its faculty certainly live up to its name. It was an honor to be a student there.

How did the MAST program prepare you for your career?

Certainly, I had more job offers once I earned the MS degree, both within and outside of my organization. I wasn’t usually even looking for a job, but people in my network would hear about me. Within Georgetown, I also made lifelong friends and colleagues (both students and professors) and the alumni network is great for finding career and research opportunities.

Certainly, having gone to Georgetown helped me in pursuing a Ph.D. Most importantly, the professors were like family. I felt like my professors cared about me and they helped me catch up when my mathematical background was lacking.

What’s your advice for alums?

One, don’t be shy about re-learning old material. I often forget concepts and I have to review old notes (luckily I save everything, I’m very organized with my notes and assignments). It’s a good idea to review basics such as probability theory. I notice that the greatest NBA players are always practicing lay-ups on their own time (Ray Allen is one example), and the same idea applies to us all: we need to keep our foundations strong.

Two, help others. Learning math and statistics is a process. Other people will appreciate it so much if you share your knowledge and advice. Never pre-judge anyone as being “not smart” – that person was me! We all learn through persistence and practice, so I try to be genuine with those who were once in my shoes.

…to Beijing, China. I joined one of China’s top mutual funds, CCB Principal Asset Management Co., Ltd., as a financial engineering researcher in quantitative investment. After three years, I became a portfolio manager.
After working there for six years, I joined another mutual fund, Founder Fubon Fund Management Co., Ltd., where I currently work as a portfolio manager. I am also responsible for quantitative investment research of the investment department. My work focuses on developing mathematical models for portfolio management, such as multi-factor quantitative models. Recently, I have been focusing more on developing AI models using machine learning algorithms. These models are used for stock selection, hedging strategy development, and portfolio management.

Why did you choose Georgetown?

I was very fortunate to choose the MS program at Georgetown University. I completed my undergraduate studies at Washington State University with dual degrees in Mathematics and Economics. My dream has always been to work in buy-side investment. When I was about to graduate, I interned at a hedge fund in Beijing. My internship mentor told me that my undergraduate math skills were not strong enough and suggested that I pursue a master’s degree. He said it would be best to find a program focused on practical applications. I spent a week
researching graduate programs in mathematics and statistics. My main focus was whether the courses in the program were closely tied to real-world applications. Mathematics or statistics is like a language or a tool. For example, a hammer. Knowing what a hammer is doesn’t matter unless you know how to use it to fix something. I reviewed programs at over 30 universities, studied
the courses in detail, and gathered as much information as I could. In the end, I applied to two universities. Georgetown University quickly offered me
admission, and I chose it without hesitation. Choosing Georgetown not only gave me hope for my career but also brought me love. Maybe Georgetown can bring both hope and love to others too.

How did the MAST program prepare you for your career?

I believe the MAST program was very helpful for my career development. It gave me a strong foundation in mathematics and statistics for my work in quantitative investment. This program focuses on practical teaching, which helped me understand the real-world applications of every formula. It also taught me how to choose the right statistical model when dealing with complex datasets, which is very important. Another thing to mention is that most of the courses in this program require you to use programming software for learning and analysis. This greatly improved my programming skills. The practical guidance in math and statistics, combined with programming training, has made my daily work much easier. Lastly, the overall course design in MAST is very reasonable and up to date.

Each course teaches a specific skill thoroughly. For example, the Time Series course is very useful in the financial industry, where time series data is everywhere. This course gives you nearly all the skills you need to handle and analyze such data in the future. Another example is the Data Mining course, which teaches you how to gather useful data and choose the right machine learning models for analysis. These skills are extremely important in the age of AI.

What’s your advice for alums?

Be clear about your career goals and prepare for them. If you want to work in a field related to mathematics and statistics, join MAST. It will teach you everything you need to know through practical applications, step by step. If your goal is to work in financial engineering or quantitative hedge funds, the
MAST program will give you all the knowledge you need. You should also understand that many applications of mathematics and statistics, especially in future jobs, depend on programming skills. You must work hard to improve your programming ability.

When you understand both math and statistics and know how to use programming to apply them, you will achieve what you want.

…business intelligence team. My role involves leading business intelligence programs and driving cross-functional analytics initiatives. I focus on identifying opportunities for process improvements and developing methods to reduce operational risk by utilizing BI tools.

Why did you choose Georgetown?

My undergraduate degree in Financial Engineering and an internship at a finance company sparked my interest in how data analytics can drive decisions in the investment industry. I wanted to deepen my math and statistics skills to achieve my career goals. I applied Georgetown’s MAST program for its balance of theory and practical learning, focus on advanced statistical tools, and strong connections with industry professionals through its faculty and alumni network. Georgetown’s diverse culture, global opportunities, and outstanding reputation made it the perfect place to grow personally and professionally. I’m honored to have been part of such an exceptional institution.

How did the MAST program prepare you for your career?

The MAST program provided a solid foundation in mathematics and statistics, which has been instrumental in my career in business intelligence. Courses like Time Series, Bayesian Statistics, Financial Statistics, etc. combined theoretical insights with practical applications. The program enhanced my data analysis and programming abilities while fostering a data-driven decision-making mindset. Its global network of professors, peers, and alumni offered invaluable support and guidance.

What’s your advice for alums?

My advice for alums is to trust in the solid technical foundation the MAST program provides and be confident in your abilities. The skills you’ve gained are a strong starting point, and growth doesn’t stop at graduation. Keep learning, challenging yourself, and staying curious. Embrace opportunities to apply your knowledge in new ways and never hesitate to step outside your comfort zone—that’s where the greatest growth happens.