Math Beyond the Numbers: How Puzzles and Algorithms are the Backbone of NSA Data Science
April 7, 2021
Sam G’s job title at the National Security Agency (NSA) may be Research Mathematician, but that doesn’t mean he adds, subtracts, multiplies and divides all day.
“There are whole areas of math that have nothing to do with numbers,” he says. “Puzzle problems and algorithms, often called ‘discreet math,’ is what’s most important in data science.”
Growing up in North Carolina, Sam’s hobbies were reading, ultimate frisbee and playing the board game Dungeons and Dragons. And, of course, puzzles. His early aptitude for math led him to enroll in the North Carolina School of Science and Mathematics, a prestigious public high school focused on the intensive study of science, mathematics and technology.
Despite attending such a STEM-focused high school, Sam took a different path for his undergraduate studies. He earned his bachelor’s degree in mathematics at Oberlin College, a traditionally liberal arts school in Ohio. After graduating, he worked at the Census Bureau for nine months as he applied for the job he really wanted: NSA mathematician. Sam was accepted and has now been with the agency for 11 years.
“The first three years at the agency, most mathematicians, data scientists and computer scientists enter a development program,” he says.
Part of that program was being mentored by older NSA mathematicians and data scientists, Sam immediately embraced that aspect of the agency and has made ‘paying it forward’ a central tenet of his career.
“Since then, I’ve mentored more than 40 employees in various development programs,” he says.
Sam admits there has always been a little bit of a teacher inside him, and that’s probably why he’s embraced mentoring young employees so much. He also mentions it gives his career at NSA a unique flavor that no other organization could give him.
“It’s the mix of industry and academia. We’re solving problems that immediately matter, but also teaching eager students,” he says.
Sam’s job involves building software to help skilled engineers do their jobs better and faster. This usually means creating algorithm designs to figure out how they’re doing it, then listening and making suggestions. He explained that with data science, the volume of information is always the biggest hurdle to overcome.
“NSA has tons of smart subject matter experts, but there’s too much data for them to study,” Sam says. “My job is to ask which part of their job is robotic, then we make a robot for it. We want to make their job easier; sometimes that means faster, sometimes that means more accurate.”
Like his enthusiasm for mentoring younger data scientists and mathematicians, Sam is quick to point out his fondness for working with his colleagues and how that translates into better outcomes.
“My work is very collaborative,” he says. “Our team is motivated to solve problems. We brainstorm and work together. The individuals succeed when the team succeeds, and everyone knows that and acts accordingly.”
So what would Sam say to his fellow data scientists and mathematicians in the private sector that are thinking about switching to an NSA career? Having spent nearly all of his career at the agency, he touts the aforementioned ‘mix of industry and academia’ which wouldn’t be found in a purely profit-motivated environment. He also makes clear that the mission-oriented work that NSA data scientists do means you’ll see things no one on the outside will see.
“NSA has capabilities and tools not seen in the private sector because we must solve problems that don’t exist in the private sector,” Sam says.
The ‘problems’ Sam refers to are certainly related to NSA’s high stakes mission of protecting national security and keeping America safe. He can’t go into much detail, but he can say that the mission he and his colleagues support make working at NSA well worth it.
“I’m not solving theoretical thought experiments or tricking more people into clicking more ads,” he says. “I’m incredibly motivated by the mission we serve.”