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 Keith Crank, the ASA’s research and graduate education manager, at keith@amstat.org.

Contributing Editor
Kathleen Kiernan is a senior statistician for SAS. She works closely with customers using SAS and JMP in several areas, including design of experiments; linear and nonlinear regression; linear, mixed, generalized mixed, and nonlinear mixed models; and genomics. Kiernan earned her bachelor’s degree in chemistry and biology from Bethany College and has a Master of Science degree in statistics from Kansas State University.

Stores have an abundance of T-shirts, bumper stickers, and greeting cards for doctors, engineers, and teachers—even for horticulturists. But, I have never seen anything for statisticians. Statistics are used in most professions in one way or another, but it is often an ‘invisible’ occupation. I am not surprised I didn’t find out it was an area of study until taking a compulsory statistics course for my master’s degree in animal breeding. I admit, when asked what I wanted to be when I grew up, I never said “I want to be a statistician.” However, I am glad it is where I ended up.

My professors at Kansas State University inspired me toward statistics. They made the material interesting and relevant, and after my first linear models course, I was hooked. I immediately realized the career potential after graduating with my master’s degree. I interviewed several places before accepting a position in the technical buy ativan with overnight delivery support division at SAS Institute. Over time, I realized how lucky I was to find such a fascinating specialty. Not everyone is so lucky, which is what prompted me to share my experience.

My team within SAS technical support is dedicated to statistics. Although there is some overlap of responsibility, everyone has their own areas of expertise. My focus centers on linear and generalized mixed models, design of experiments, and genomics, and my job depends on questions from SAS customers. As a result, my day is roughly divided between phone duty, researching solutions to customers’ questions, communicating solutions to customers, and career development.

When a customer calls the SAS switchboard with a statistical software question, they are transferred to the statistician assigned to phone duty. If the statistician on phone duty cannot resolve the question, they either file it for later research or route it to the statistician covering that specific area. For my areas, I can usually find the solution in my personal usage notes and sample programs of explanations and resolutions. Other times, the questions require research through SAS resources, coworkers, statistics books, or papers. More complicated issues require not only research, but possible consultation with a software developer. The developers are great to work with; they invite questions and usually drop their own work to treat the question as a priority.

Documentation is a big part of the job. SAS technical support documents the questions from each customer along with the corresponding solutions. This documentation serves two purposes. First, we keep track of frequently asked questions so areas of concern or suggestions for new features can be communicated to the software developers. We also help write and review any new documentation that results from the suggestions. Second, we write usage notes with explanations, solutions, and sample programs that use existing or simulated data. Keeping a complete record of information in our files goes a long way in freeing up our time later.

I am well suited to this career for a variety of reasons. While my main areas of focus in college were mathematics, statistics, and education, I also am able to use my background in chemistry, biology, and genetics. Additionally, I am at an advantage because I was a graduate teaching assistant and taught undergraduate statistics courses. I am able to explain statistics to nonstatisticians; being able to speak clearly without the use of jargon or acronyms is critical to communicating with customers.

The opportunities and challenges of my job are endless; boredom is rarely a problem and career development is nonstop. Because I learn new areas and applications as software is created or revised, I need to be comfortable with the procedure syntax, running the procedures on different operating systems, and interpreting the results. I have increased my programming and communication skills, which are sometimes just as important as my statistical skill set. I enjoy the new and continuing challenges. While the number of questions I am able to answer off the top of my head has increased over the years, I still have hard problems to resolve. I usually find a solution within a couple of hours (or days) using research and programming. There is no way to know everything, of course, but the challenge is always there.

Being able to learn from so many types of people is a truly great advantage of working in technical support. The relationships I have built with coworkers, developers, and customers have made my 18 years at SAS enjoyable. I have never-ending opportunities to talk with engineers, researchers, physicians, scientists, and statisticians from other industries. As I help with the design or analysis of their experiments or studies, I gain a greater understanding and appreciation for quality control in building cars and planes and developing new drugs.

My advice to someone thinking of a career as a statistician in a software company is to think about what you want to do before you start your career so you can take the appropriate steps as you go along. If you are interested in becoming a developer, I recommend you get your PhD and experience in developing software. However, a statistician with a master’s degree has many opportunities in the technical support division of any software company.