The Center for Naval Analyses (CNA), a Federally Funded Research and Development Center (FFRDC),is sponsored by the Department of the Navy and headquartered in Arlington, Virginia. CNA's mission is to help Navy and Marine Corps leaders ensure America's defense in the 21st century. CNA is unique because of its real-world, empirical, and data-driven approach to operations analyses and use of data scientists as expert observers of military operations. CNA is the nation's oldest operations research organization with lineage tracing back to World War II (1942) when CNA scientists went to sea aboard Navy ships to observe and analyze anti-submarine warfare operations in order to help defeat German U-boats. Its research staff has diverse educational disciplines with nearly 70% with Ph.D. degrees and 92% having graduate-level degrees.
Tim Kao is the Vice President of Data Science, CNA. He has served in the United States Marine Corps for 20 years, including two combat tours to Iraq and one to Afghanistan. During those two decades, Tim served in artillery, special operations, space, jungle warfare, and operations analysis commands. He received a B.S in Operations Research from the Air Force Academy, an MBA from the University of Colorado, and a Master's in Operations Research from the Naval Postgraduate School. Tim started working at CNA in 2015 and is currently the Vice President of Data Science. As the VP, he has the privilege of leading nearly 30 data scientists that are collaborative partners with Navy and Marine Corps sponsors and committed to supporting America's naval services.
Data scientists rightfully focus on relationships between feature and target variables. However, Tim understands that leadership, even for data scientists, fundamentally is about relationships with people. As a young jump master instructing parachuting at the Air Force Academy, Tim quickly learned that the safety and success of personnel learning to jump out of airplanes depended on the trust and relationship they had with him as their instructor. If that was lacking, the probability of having students that refused to jump increased significantly. In the Marines, Tim worked for some great leaders and some bad ones. The difference between those two types of leaders came down to the relationships those leaders were able to establish with those people they led. Leading data scientists is no different. Tim values a data scientist's technical skills, but their ability to exhibit the extremely hard to master 'soft skills' is just as important. That is what CNA looks for when hiring data scientists (and they are hiring!www.cna.org) and it contributes to the team's success.
Tim recognizes that the ever-evolving discipline of data science requires a constant refresh on emerging algorithms, technologies, and processes. He says that when he joined CNA, he was coming from a USMC assignment as the commander of the only jungle warfare training center in the Department of Defense as well as a recent deployment to Afghanistan. While Tim was able to use some of his data science knowledge to support those military units, many of my data science skills quickly atrophied, as he did not use them regularly. According to him, overcoming this challenge required a growth mindset to catch up quickly on emerging machine-learning techniques and code. This continues to be a challenge today as data science evolves every day. "A growth mindset is critical for a data scientist to have continued success," highlights Tim.
For Tim, the two most important characteristics data science leaders need to have are being curious and caring. He adds that being curious is important because leaders won't know everything, but need to know enough to search out an answer through research and collaboration with others. Being caring is also vital because Tim believes in the truism that no one cares how much you know until they know how much you care. Tim asserts that "Leading data scientists really isn't much different than leading Marines in combat.You have to know yourself (what are your data science capabilities), know your enemy (what is the problem being solved), and take care of your troops (data scientists) so they want to do a good job for each other and you."
One of the ways Tim addresses the needs of his customers is to apply agile and scrum techniques to help solve data science problems. At CNA, Tim uses concepts like developing minimum viable products (MVPs) to iterate with its Navy and Marine Corps project sponsors. These sponsors are an integral part of the creation of any data science solution CNA is developing. CNA not only works with them on the user interface, but collaborates with them to understand the data, how it is collected, and other assumptions needed to create a useful model. A successful data science effort requires both superb data scientists and a close partnership with the Navy and Marine Corps end-users of the analytics.
Tim is adamant that data scientists need to leverage disruptive technologies in their work. Like other professions, but perhaps even more so, data scientists want to do innovative and meaningful work. It's incumbent on data science leaders to provide them that opportunity. He adds that even if data scientists thinks they are too busy doing work to learn new things, by definition, there is an inherent risk from overlooking disruptive technologies. That risk will manifest itself by not being very busy much longer as their work will go to people that have learned those new things.
According to Tim, much like a rising tide lifts all boats, such is the case for many data science organizations in this current era of data science being very much in vogue. The data science leaders that separate themselves in this type of environment are the ones that can couple the hard skills (i.e. statistics, programming, machine learning) with the soft skills (i.e. communication, empathy, collaboration). According to Tim, at CNA, the team works on both sets of skills every day so it can help provide a competitive advantage for America's defense.
"Don't forget about your people" asserts Tim. According to Tim, most data scientists spend more of their waking hours at work than they spend at home with their families. Tim insists that the data scientists on his team do everything they can to help their colleagues look forward to coming to work every day. Tim asks them to create an environment that provides the psychological safety for people to share their ideas and problems. According to Tim, data scientists get better solutions and outcomes if they build an inclusive environment in their workplace, where their team will work as long and as hard as it takes to accomplish the mission and no longer and no harder. He concludes by saying, in the Marine Corps it is "Mission first, Marines always" and at CNA I've adopted that mantra to be "Mission first, People always."
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