Chris Diehl’s father worked for the Air Force so from a young age, Chris wanted to be a fighter pilot.

“One day I woke up and was like, what am I thinking? I don’t even like roller coasters,” he says. Instead, he got interested in international relations, foreign affairs, and special ops, and thought the intelligence community might be a good fit for him.

“Then I was like, well, how do I contact them?” he recalls. “In the one case with the CIA, I literally just wrote a letter, put it in an envelope, wrote ‘Central Intelligence Agency, Langley, VA’ and I chucked it in the mail.”

One day, he opened up the mailbox to find a nondescript envelope that turned out to contain a full-color brochure with an application from the Central Intelligence Agency. Unfortunately, he wasn’t old enough to apply—but he found similar programs at the National Security Agency and the Defense Intelligence Agency. He applied and was accepted to the DIA, which offered to pay for college in return for a 4.5 year commitment after he graduated.

He went to Carnegie Mellon University and majored in Electrical and Computer Engineering. At the end of his undergraduate degree, the DIA asked him to do a Master’s degree. “I was getting ready to go to Stanford, when one of my professors at CMU asked why,” he says. “I told him I couldn’t get any school to give me money because I wasn’t going on to get a Ph.D. because I had this commitment [with the DIA].” A few hours later, that CMU professor called him and offered him funding to stay and work on a project to study and model the propagation of electromagnetic waves inside of buildings.

“It wasn’t my first love, but $25,000 in the black vs. $45,000 in the red, I said I’ll stay,” Chris says. The same story repeated itself a year later, and he stayed on at CMU for a Ph.D., which he finished in December 2000.

He didn’t finish out his commitment to the DIA. He paid his tuition back and went to work as a research scientist at the Applied Physics Laboratory at Johns Hopkins University, a defense laboratory, for the next 8.5 years.

“That was a better fit, but there were still struggles,” he says. “I was like, ‘Let’s do more, let’s go faster.’ Halfway through my time there, I was this close to walking out the door.”

After some time thinking about what was important to him, he says, he realized this wasn’t the path for him. “I took 3-4 months to say, ‘What’s going to get me out of bed in the morning?’ I considered leaving technology, going into policy, going back into intelligence,” he recalls. “One morning, I woke up and looked at my reading pile, and the last 4 books I read were about terrorism. I decided to think about that more and integrate that into my job.” Specifically, he was intrigued by a book he’d read on social network analysis, a field he never knew existed.

“Basically, I’ve been pursuing the interesting problems on the boundary between my world as a machine learning researcher, and social network analysis ever since,” he says.

He started working at the Lawrence Livermore National Lab instead, working on how language patterns reflect the nature of a given social relationship. “I had built a machine learning algorithm and, with a colleague, built a prototype to allow you to interactively map out social networks from a large collection of email,” he says. “We discovered, almost by accident, that the words that are very compelling and discriminative and help you identify these relationships are function words like conjunctions, prepositions, and pronouns—words that in traditional information retrieval systems, we just throw away.”

Still, he felt he could have more impact in the private sector. So, just three months ago, he joined Jive Software—an enterprise communication, collaboration, and social networking software company—as their first, and only, data scientist. His friend’s startup, which Chris advised, was acquired by Jive, and he convinced Chris to join as well.

“The Jive platform is used by, like, 15 million people,” Chris says. “Talk about impact.”

Jive has never had a data science component to it before, Chris says, so “we’re learning about one another.”

His obsession with math and computers started early, despite his aspirations of being a fighter pilot. He used to write programs on his first computer, a TI-99/4A. He wrote a program that would find the optimal solutions to magic squares and print the solutions to his dot matrix printer. And he spent his high school summers working at the Naval Research Laboratory in Washington, D.C., surrounded by genetic algorithms and evolutionary computation.

“Math and statistics,” he says. “I can’t get enough of that.”