While working full-time in Northern Virginia as a consultant in technology, management, and marketing analysis for over a decade, Tigran Markaryan also teaches statistics at George Mason University as an adjunct professor.
A zeal for teaching and an appreciation for education bring Markaryan back each semester.
“I love teaching, so as long as I can do it combined with my work, I will do it,” he said, adding that despite the difficulty of teaching on top of working full-time, he enjoys the challenge. “One of the best ways to learn something really deeply is to teach, so it's a challenge of explaining some well-known concepts in new ways, in more efficient and effective way for my students.”
Markaryan teaches applied statistics, applied probability, biostatistics, and doctorate-level probability. He also teaches a summer math review course on Saturdays in the beginning of Fall semester for any Department of Statistics students wanting to brush up on such topics as calculus, set theory, and matrix algebra.
Markaryan’s first degree was in pure mathematics. He went on to earn another three master’s degrees, in business administration, applied math, and statistics. He was excited to learn from his former colleague Professor William Rosenberger that he could pursue a doctorate part-time at George Mason as he worked full-time. Markaryan defended his doctoral dissertation in statistics at George Mason in 2009 and has been teaching as an adjunct professor since 2010.
As an analytics consultant, Markaryan has worked on optimizing marketing investments for Fortune 100 organizations, building forecasting systems and decision support tools, and performing survey research for federal clients. Currently, he is leading the analytics practice for a workforce management organization that provides a Software as a Service (SaaS) platform for restaurants globally.
Markaryan tries to bring real-world examples informed by his work into his teaching. He also tries to pass on practical advice to his students regarding non-technical skills, such as tips on effective presentation.
“We are all guilty as analytics people or statisticians; sometimes, we focus too much on the technique and not as much on who is going to consume the results,” he explained. He urges his students to consider the proper way to package their results for a given audience. He teaches them to consider, “What's the purpose of the model? Who is going to use it? How do we help them understand the model, and the recommendations, and how to act?”
“I think the majority of people in my experience who are technically really good sometimes just jump on the technique,” he said, adding that it’s just as important to be able to explain the main finding of an analytical technique as it is to understand the technique in the first place. Master’s students in Markaryan’s Applied Statistics II class complete fifteen-minute presentations describing their methodology, results, and recommendations. And odds are, they'll put Markaryan’s advice to good use.