As Leonardo da Vinci applied his intricate knowledge of human anatomy to create timeless art, so 21st-century technology developers must combine technical skill with multi-disciplinary insight.

12/14/15
-by Denis Nekipelov, Associate Professor of Economics and Computer Science at the University of Virginia.

What skills do you need to get hired by top tech firms today?

As a professor of economics and computer science, I hear this question more than any other from students, and it’s the top question I ask of colleagues working at today’s major tech firms. Their answer is simple and daunting: “We want the full package.”
Leading-edge tech companies are defined by consumer-facing products and internal “startup-style” culture. Thriving in that environment requires knowledge of data sciences and social sciences. Graduates interested in tech will certainly need practical knowledge, but many will also need abstract theory. They must be able to appreciate the details and the big picture, to code and to codify.

If you look at any category in an app store, you see top mobile apps that get thousands of downloads and reviews and a very long tail of apps that barely get any consumer attention. Those forgotten apps have failed to appeal to enough people, often because developers did not analyze demand accurately or strategically monetize and market the product. Knowledge of human behavior — supported by science — can predict the success of digital products. Such knowledge comes in large part from the social sciences and humanities.

For example, a graduate who understands fundamental concepts like the Nash equilibrium — a game-theory concept holding that players’ strategies are based not on logic alone but on knowledge of other players — will better understand how consumers behave. A graduate who studied linguistics will be better equipped to develop artificial intelligence-based applications, which rely on a deep understanding of language. A graduate who studied music or art will be ready to design more compelling virtual environments.

This is not to say, though, that technology firms need purely social scientists. Tech firms’ startup culture means that new IT products, even larger ones like Microsoft Windows or Mac OS, are developed by very small teams. There is no room for a theorizing economist or a sociologist. The development process requires constant testing and changes to source code. The urgency increases when the product is first released: Early bugs must be detected and instantly fixed. Every team member needs to understand the technology at a minute level.

Consequently, the most compelling hire will be at once an engineer and a social scientist — a “New Renaissance Man.” As Leonardo da Vinci applied his intricate knowledge of human anatomy to create timeless art, so 21st-century technology developers must combine technical skill with multi-disciplinary insight. These employees are the “full package” — social scientists who can articulate principles of consumer behavior and manage complex computing infrastructure. They are computer scientists and engineers who can use economic models and sociology theory to accurately analyze, prove and meet consumer demand.

As an educator, I have to admit that the American higher education system is still far from developing that “New Renaissance Man.” Too often, the education community interprets demand for integrated fundamental knowledge as demand for number-crunching skills combined with some literacy in economics or business. This has led to a proliferation of “business analytics” and “data analytics” concentrations that focus narrowly on technical competence. This shortsighted strategy could lead to the development of skills that become antiquated before students graduate, as technology responds rapidly to changing demand.

The most employable graduates will have knowledge beyond specific infrastructure, programming language or statistical software. Their knowledge will be fundamental.
My advice to undergraduates would not be to take a class in Python, but instead take a class in the theory of algorithms. Similarly, do not take a class in online auctions; instead, take a class in game theory. Many undergraduates, especially those who find jobs with the Googles and Microsofts of today, already follow this strategy. However, they need more institutional support.

My advice to institutions is to develop more integrative interdisciplinary programs to adequately address 21st-century industry demand for talent. At the new Data Sciences Institute at the University of Virginia, we have found success in creating centers that foster interdisciplinary collaboration — one focuses on big data ethics, law and policy, another on how data science is transforming knowledge. We have also used reading groups and lecture series to gather faculty, students and private sector leaders in technology, economics, public policy and other key areas. We want students to not only develop and create technology, but also thoughtfully discuss its implications and accurately predict its outcomes, with sound social science backing up their conclusions.

Such efforts should be but the beginning, as the new landscape of the technology sector calls for increasing involvement of social science in places previously exclusive to engineering and computer science. Technology is changing at a rapid pace, and universities must prepare a skilled workforce that can easily adapt to even the most dizzying rate of change.