This column is written for statisticians with master’s degrees and highlights areas of employment that will benefit statisticians at the master’s level. Comments and suggestions should be sent to Megan Murphy, Amstat News managing editor.

Contributing Editor

Sheila Rosenberg recently began working as a data scientist at Kaiser Permanente. She completed a master’s in applied statistics from Colorado State University and a PhD in neuroscience from the University of Southern California. She also completed postdoctoral training in neuroscience, bioengineering, and clinical research at the University of California, San Diego.

I always enjoyed math when I was growing up. When I was in college, my mom wisely suggested I pursue a career in something math related. I remember telling her I liked the idea, but I wasn’t sure how to use math to help people. As I discovered later, there are clearly many ways to use math to help people, and there are several careers—including ones in statistics, engineering, etc.—that provide this opportunity.

At the time, I hadn’t made that connection, so I went to graduate school to study neuroscience instead, with the goal of developing new therapeutic treatments for diseases. I began by examining molecular strategies for treating diseases and gradually ventured into translational, bioengineering, and clinical research, where I had the opportunity to help develop and evaluate therapeutic treatments for a range of medical conditions.

Interestingly, this career path kept leading me back to the need for quantitative approaches. As soon as I started working with human subjects, I discovered I needed statistics to balance my groups, determine the relationship between sample size and power, optimize my study designs, and analyze my data. The exciting potential for simultaneously analyzing physiological, behavioral, and clinical data highlighted the need to learn approaches to evaluate multi-modal data and draw useful conclusions.

I was fortunate to work with a postdoctoral mentor, Todd Coleman, who exposed me to myriad opportunities for using quantitative methods to uncover biological mechanisms and, ultimately, advance medical care. I could see the value of being a scientist who collaborated with analytical experts. But I also found myself feeling a little envious of the statisticians and engineers I met, because they had the opportunity to develop and use interesting quantitative methods to analyze data.

Shortly after starting a position in which I was designing, implementing, and analyzing research studies in a neurological rehabilitation hospital, I kept finding myself with questions such as the following:

• What is the right analytical method to use to analyze this data?
• What kind of power do I have with these small groups?
• How do I make predictions about which patients might benefit from certain treatments based on their physiological results?

In my efforts to answer these questions, I struggled to know what resources to use and became lost trying to follow the more mathematical explanations I discovered online. I decided that if I wanted to continue to advance and optimize my scientific endeavors as an independent investigator, I really needed to learn more math and pursue additional training as a statistician.

Going back to school was hard—harder than I expected. But worth it. I just completed my master’s in applied statistics about a month ago, and I am now actively searching for a job. While I don’t know yet what my next career phase will look like, I believe pursing the master’s was completely worth it and came with many benefits (some more unexpected than others). Here is what I learned through the process and reasons I would highly recommend a master’s in statistics:

Distance learning programs offering flexible schedules make a master’s degree accessible and adaptable. From what I have seen, the number of graduate programs offering a distance learning option is continuing to increase. Many of these programs seem willing to accommodate students who want to work and go to school or take classes full time. This means you have the flexibility to find a program with a curriculum and schedule you like (hopefully) without having to relocate (in case that isn’t an option). There are certainly downsides and drawbacks to not being in the classroom, but video lectures work pretty well and provide the opportunity to rewind and review material. Some professors offer options like office hours over Skype. And many schools, libraries, and testing centers offer proctoring services for you to take your exams locally. Overall, I think the system works well and likely will only improve with time.

The statistical community seems very welcoming and friendly. In my experience so far, statisticians seem to be awfully nice overall. For example, I attended a local San Diego Chapter event and former ASA president Jessica Utts gave a talk. I ran into her later and she was extremely friendly and approachable. I’ve also been amazed at the amount of interaction that takes place through the ASA chapter and section emails. There seems to be many opportunities for students and recent graduates, as well as outreach globally (with organizations like Statistics without Borders).

You can make great new friends with unique perspectives. I interacted with great classmates through the online discussion forums my courses offered. I also was extremely lucky to form a study group with three other distance-learning students, all of us located in different places with different backgrounds and careers at different stages of our lives. This group made the program infinitely easier and more enjoyable. We had the chance to help each other with assignments and work together on group projects. It was great to have moral support and humor and advice from each other, and I would never have predicted I’d leave the program with these great new friends.

You will develop a fun and exciting set of tools and build a quantitative foundation. I was lucky to find a program at Colorado State University focusing on applied statistics while emphasizing quite a bit of theory and underlying calculus/linear algebra, which was what I wanted. I felt this combination has enabled me to continue to learn on my own after graduating, because I can speak the mathematical language in a way I wasn’t able to before completing the master’s. For me, the coursework was challenging, but also extremely interesting and intellectually satisfying.

You will learn how to code (and have to develop a lot of patience while trying to code). I had never coded in SAS or R before starting the master’s program. It was a bit of a rough learning curve initially, but like learning any language, immersion was definitely effective. The practice I gained with coding was both insanely frustrating at times and incredibly valuable. Plus, it exposed me to the vast resources and advice for coding available online. As my study group often remarked, it’s also amazingly satisfying when you find that one silly error in the code you’ve been stuck on for hours and get the code to compile successfully!

You will expand (I think!) your career opportunities. I don’t have a new job yet, but I’m now qualified to apply for a fresh set of jobs as a result of the master’s degree. I’m hoping to combine my previous experience in research with my statistical training and continue to work on the discovery and development of new therapeutics. It’s thrilling to have a whole new arsenal of strategies for analyzing biological data, but it’s also exciting and useful to know having a master’s in statistics should allow me to explore new fields if I desire. The statistics community provides an exciting arena, where people may work in many environments with different goals but come together and speak a common language to provide ideas from disparate fields that might be useful to your project. There also appears to be ongoing potential to move between fields because of the relative generalizability of many statistical techniques.

If you are like me and you enjoy variety and the opportunity to try new experiences, I think you’ll find a master’s in statistics rewarding. You’ll also be excited to hear the quote by John Tukey really does appear to be true: The best thing about being a statistician is that you get to play in everyone’s backyard.