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Telling Data Stories: An Interview with CIA’s Dr. Calvin Andrus

Dr. Calvin Andrus—a 30+ year CIA veteran—has made a career of discovering patterns in data. From covering European politics around the fall of the Berlin Wall to pioneering cloud computing at the Agency, Calvin has used his subject matter and technical expertise to help answer pressing national security questions. Calvin was one of the first winners of the Director of National Intelligence’s Galileo Awards—an annual intelligence community competition on workplace innovation—and is the first CIA employee who has been invited to TED.

We sat down with Calvin to learn more about his work and the role of data science at the Agency. Here is an edited and condensed version of that conversation.

Can you share some professional highlights?

I was working in the Directorate of Intelligence (now the Directorate of Analysis) Office of European Analysis when the Berlin Wall fell. After the Wall fell, I was part of a group that worked on the rise of democracy in Eastern Europe. That whole time period was very exciting, interesting, and professionally fulfilling.

Later, winning the first Galileo Award in 2004 for my paper on blogs and wikis opened a lot of doors for me. I lead a couple of teams that worked on virtual worlds and mixed reality. The work was theoretical but engaging and interesting. More recently, I partnered with others to bring cloud computing to the Agency. All of those have been very interesting, fascinating, difficult, challenging, and rewarding problems.

Analysis, IT, and innovation have all been prominent themes in your career. How do those three domains intersect at the Agency?

I live in that intersection; that’s where I’ve found my niche. I work best in the junction of different disciplines as I move from assignment to assignment. Analysis at this Agency is of supreme importance, and--like everyone else in the world--we have more data coming to us than ever before. We need to make sense of that data for the sake of our national security. Innovation on the IT front is required to enable innovation on the analytic front. There are IT infrastructure, tools, and methods that need to be put into place. The data needs to be compiled and communicated in such a way that it is available and accessible for analytic use. In that way, IT innovations enhance our ability to do the kinds of analysis that we are required to do.

You are currently in charge of outreach and training for the Agency’s data science hub. What is a typical day like?

My responsibilities include creating a training program for our data scientists and cultivating relationships with data scientists outside of the Agency. My days are really consumed by those two activities plus a little bit of mentoring of junior data scientists. My team thinks through what our data scientists need to know and what they need to learn. For example, we consider which data science topics should be studied in courses taught external to the Agency, and which topics should be designed and taught as internal courses. On the outreach side, our team enables connections with data scientists on the outside to engage on particular problems.

Data scientists are a hot commodity these days. Why should a data scientist choose the Agency over a startup or a high-powered tech company?

There is this irony that the best minds in America are working on search engine optimization (SEO) and trying to get better ads to you and me. That’s just not that interesting. If somebody wants to use his or her mind on something really important that makes a real difference in this world, they come to work for us. Government employees don’t make as much as people who get stock options in Silicon Valley, but the people in Silicon Valley just don’t often do the kinds of interesting, meaningful work that we do. There’s nothing like working for the CIA.

What do data scientists do at the Agency and how do you see their role changing over the next five years?

Our data scientists work hand-in-hand with mission and business elements of the Agency. We have data scientists embedded in the analytic, operational, and business realms. They are members of teams who bring data analysis to bear on mission and business questions. What we want to do is to help inform decisions with the best data and analysis possible. Maybe it’s a business process that can be improved, or understanding the flow of illicit material around the world, or exploring some newly acquired data. There are a lot of different ways our data scientists work. What is common among them is they usually write computer programs and perform mathematical or statistical modeling of the data. They then convey the results to their non-data scientist partners. Our data scientists embed their findings into the story of intelligence.

You have previously commented that whoever masters massive data will win the IT arms race. How do you think we are doing?

I think we are doing quite well. There is always room for improvement, but we are able to analyze data using massive parallel computations and sophisticated models. This was just not possible in the past. Many of the successes in the war on terror have been the result of sophisticated data analysis.

What advice would you share with people who aspire to become CIA officers?

My advice would be to remember what the CIA is and does. We protect the nation and the Constitution from foreign threats, so we have to know the world. That is our domain. Anybody who wants to work here needs to know about the world beyond our borders--as well as cutting edge methods and tools used across disciplines (such as economics and history). We need to know the substance, the methods, and the tools as best as we can to help our national policymakers protect the American people.

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Posted: Aug 16, 2016 10:59 AM
Last Updated: Aug 16, 2016 10:59 AM