How Sarah’s Private Sector Path Led to a ‘Seat at the Table’ as an NSA Data Scientist
October 12, 2021
If you think the path to an NSA career in data science is strictly through mathematics, statistics, computer science or engineering … you’re wrong.
“I’m a social scientist and a behavioral scientist,” she says.
Growing up in Florida, Sarah was interested in photography and other artistic endeavors – hobbies that don’t necessarily scream ‘NSA scientist.’ However, her story reflects the reality that a multitude of backgrounds – from astrophysics to zoology to liberal arts – can be the origin of a career in data science.
Sarah attended nearby Florida State University and earned a Bachelor of Science in Psychology. She had an interest in behavioral analysis and studied that subject further at the Florida Institute of Technology, eventually earning a Master of Science in Organizational Behavioral Management.
While earning her master’s degree, Sarah had her first taste of actual data science at work in the field. She analyzed and worked with airport security officers to see if they could increase their situational awareness. In other words, by amassing enough data about successful airport security officers, that information could then be shared to improve the practices of every airport security officer.
That experience led Sarah to fully embrace data as a way to solve problems and improve efficiency in all areas of life … but especially law enforcement. She continued this theme at her next academic step, attending Western Michigan University and earning a Ph.D. in behavioral analysis.
Her field work during that period entailed working with the local police department in nearby Kalamazoo, Michigan. There she helped officers increase their proficiency in data entry for crime evidence. The idea being the more data, the more evidence the officers had to put away the bad guys. The officers Sarah worked with were skeptical at first.
“I had to keep telling them that I wasn’t there to sell them something,” she says. “But now there are more data scientists in law enforcement than ever before.”
After completing her doctorate, Sarah worked in the private sector, first at Northrop Grumman and then at Booz Allen. However, her goal remained to continue what she started during her academic years and use her behavioral and data skills in law enforcement. After a few years as a data analyst at the Department of Homeland Security, she then accepted a position as a Lead Data Scientist at NSA.
Sarah has now worked at NSA for nearly five years and describes her job this way:
“As a Lead Data Scientist, things change on a day-to-day basis, but I oversee obtaining requests for items, such as metrics, and monitoring our workflows,” she says. “I’ve also recently been asked to lead the machine learning efforts of incorporating additional analytics into a current workflow.”
So having worked as a data scientist both in the private sector and as a civilian at NSA, how does Sarah compare the two experiences?
“I have a seat at an important table that not all other data scientists have in this community,” she says. “I feel that when you’re a civilian data scientist, people listen to your methods and results with open ears and eyes, which is great. When I worked in the public sector, I never really felt ‘heard,’ so to speak.”
The aspect of ‘feeling heard’ has been crucial to Sarah’s continued job satisfaction and the ‘seat at the table’ that NSA provides is more important than just compensation.
“Anytime I talk to colleagues in the private sector, I find out they make a little more money than I do, but also, they don’t have the seat at the table that I have,” she says. “I have much more leeway in terms of determining processes, procedures, funding and hiring.”
Sarah also says that she’s had more leeway in the addition of new skills to her already impressive resume. Even though she describes herself as more of a ‘social scientist,’ Sarah has increased her knowledge in computer skills, specifically the programming language Python.
“It was a challenge to learn [Python], but I was highly motivated to learn it and was supported,” she says.
Early in her academic career, Sarah saw firsthand the impact data could have making her fellow citizens safe, whether through airport security or law enforcement. That passion took her to NSA, and she hopes her fellow data scientists with private sector experience consider following her lead.
“My advice for data scientists exploring a career at NSA is to be curious about data and be open to change,” she says. “You’ll get to learn new things and work with awesome colleagues.”