Thomas McAndrew, (Biostatistics, MS 2010; Mathematical Sciences, PhD 2017)
Thomas McAndrew received his Ph.D. in Mathematical Sciences in 2017 from the University of Vermont, an MS in Biostatistics in December 2010 from Georgetown University, and a BS in Biomathematics in 2009 from University of Scranton.
He is a computational scientist working at the intersection of biostatistics and data science. In his past research, he studied ensemble models for infectious disease forecasting, expert-judgmental models, and crowdsourcing. In a leadership position in industry for 2 years, as Associate Director of Biostatistics, he honed his ability to design and analyze multinational clinical trials and coauthored over 60 manuscripts in cardiology. He is currently completing his postdoctoral fellowship of Biostatistics at the University of Massachusetts at Amherst. He will join the faculty as Assistant Professor at Lehigh University in the College of Health this summer 2020.
How did you get interested in studying Biostatistics? What was your background before Georgetown University?
I chose to study Biostatistics because I wanted to learn how I could apply mathematics and statistics to specifically biological problems. Before the MS program, I earned a BS in Biomathematics and took a probability/statistics class in my last year. The class spent time showing students how to use mathematical skills to explain our world. I was inspired by how statistical models can explain complex biological phenomena and felt that the faculty at Georgetown too were passionate about how to explain our world using mathematics and statistics.
What did you love most about the MS program?
I liked how the MS program balanced theory and applications. Classes give students a foundation in statistics and probability, but also emphasize applying statistical concepts you learn in the classroom to real data sets. The blend of statistical fundamentals and emphasis on applications I learned at Georgetown allowed me to easily transition back and forth from industry to academia—I didn’t have to pick industry or academia. Georgetown helped give me the tools to explore both.
My favorite class was probability [BIST 510], taught by Dr. K. I felt like a solid understanding in probability gave me more confidence in statistics.
What was challenging about the program?
A challenge for myself, and I expect for incoming students, was juggling between classes that focus on statistical theory and programming. It may be a challenge and feel overwhelming now, but in the long run the MS program is an excellent blend of theory and applied work that will make you a strong candidate for a PhD program or industry/government work.
Please describe your current work and job responsibilities.
In industry, as a Biostatistician, I spent time working in statistical genetics and then clinical trials. As Associate Director of Biostatistics for the Cardiovascular Research Foundation, I honed my ability to design and analyze multinational clinical trials and coauthored over 60 manuscripts in cardiology.
[In academia,] as a postdoctoral fellow of Biostatistics at the University of Massachusetts at Amherst, I work with Nicholas Reich on forecasting infectious diseases like seasonal influenza and COVID-19. I had two major goals during my postdoctoral fellowship: expanding on techniques used to combine statistical forecasts of seasonal influenza and explore how we can use statistical models to aggregate expert predictions of an outbreak. Currently I spearhead a project that aggregates over 37 expert predictions on various dynamics of the COVID-19 outbreak.
Recently, I accepted a faculty position at Lehigh University in the College of Health. As Assistant professor, I will spend my time pursuing cutting-edge research designing novel adaptive ensembles to forecast infectious disease, and teaching undergraduate and graduate students about statistics, machine learning, and data science.
How do you use what you learned in our program in your current work?
One of the strengths of Georgetown’s MS program was statistical communication. The MS program emphasized exploring internships and…a class was offered on statistical consulting [which is presently incorporated into BIST 545 “Quantitative Data Analysis & Reporting”]. The class showed how to collaborate with researchers who are not statisticians, ask the right questions, and formulate results in a simple and clear way. The internships I participated in while at Georgetown allowed me to try out these concepts learned in class, and more importantly how to explain them to others. I learned how to clearly communicate statistical concepts to others, and that skill was, and is, essential to my success.
What advice would you give to current and prospective students?
I would recommend students spend more time learning how to translate data into results via statistical programming. In industry I devoted quite some time hiring biostatisticians. One of the characteristics that separated good biostats from great biostats was strong programming skills. Understanding every possible brand-new statistical technique is not as important as having a solid foundation in data manipulation. I would recommend students spend time in SAS, R, and Python, learning how to combine and manipulate data–those are essential skills.
[My second] advice to students and recent alumni is to be honest. Many times, and especially in industry, I found statisticians afraid of telling a coworker or collaborator “I don’t know”. It is important to know your limitations, take a break to study a topic you’re not familiar with, and give a succinct and clear answer.
“Insider” info: [As an interviewer], I would purposefully ask a prospective employee a difficult question and listen to how they answered. The goal wasn’t to intimidate them; the goal was to understand how they handled answering a question that was (understandably) too difficult to answer in a 20 minute interview.
Why did you want to continue with a PhD program?
After earning my MS, I spent time in industry working in statistical genetics and clinical trials. Industry taught me how statistics is used to translate data into results, and in particular, I spent the majority of my time collaborating on research papers. But only a year or [two later]…, I found myself asking statistical and mathematical questions about data I was working with that would require a more advanced degree. [My PhD studies]…explored weighted networks and how they can be used to investigate a diverse range of topics: the robustness of power systems, how humans write about causal concepts, and how networks of people can be used to solve problems. The biggest lesson from my PhD, by far, was how to put together a research paper and how to write.
After my PhD, I was offered a position as Associate Director of Biostatistics at the Cardiovascular Research Foundation, the same company I worked for before I left to earn a PhD. The plan was not necessarily to return to industry; I thought it would be fun to return to the research area that inspired me to pursue a PhD in the first place and lead a team of biostatisticians developing statistical analyses for novel clinical trials. After 2-3 years, I was again bit by the research bug [which lead me back to academia]. I am currently completing my postdoctoral fellowship of Biostatistics at the University of Massachusetts at Amherst and will join the faculty at Lehigh University in the College of Health as Assistant Professor.
How is working in industry and academia different?
The most striking difference I found between working in academia and industry was mentality. In academia you’re allowed to focus on pushing the boundaries of statistics. Spending days, weeks, and even months on a single project is very reasonable—you’re exploring new concepts others may not have yet. Industry, in my experience, focused on productivity, efficiency and communication. I was so successful in industry because I could communicate tricky statistical concepts to others.
My jumps back and forth from industry to academia were not as difficult as many people made me believe. My advice to others thinking about transitioning from industry to academic or vice-versa is that it’s ok. When you choose one path or the other, you’re not stuck there. We’re statisticians. Take time to explore paths, collect data on your own experiences and which field you like better, and after sampling both paths—make the right decision for you.
What did you love about Georgetown University and DC?
The wealth of opportunities and internships available to aspiring biostatisticians. The DC area is home to many government institutions and companies that employ biostatisticians. The faculty at Georgetown are well-connected and very supportive of students pursuing internships in the area, and I would strongly suggest students take advantage of those opportunities.
Anything else you’d like to add?
Students should take advantage of all the amazing faculty at Georgetown University’s Department of Biostatistics. Spend time talking with as many faculty as you can. The faculty have a lot of experience in academia and industry, and they made a major impact on my continued success in the field.
What is your favorite hobby?
My favorite hobby is taking my dogs: Banjo, Fiddle, and Kazoo, for walks.
Any other interesting information you’d want to share with us?
Those interested in my work can visit my webpage at http://www.thomasmcandrew.com/ and please feel free to email me at firstname.lastname@example.org
Updated April 2020