RESEARCH COLLOQUIUM ON COMPUTATIONAL SOCIAL SCIENCE/DATA SCIENCES – Scott Watson – Flying into the Future: Building a Career in Data Science Outside Academia

When:
February 21, 2020 @ 3:00 pm – 4:00 pm
2020-02-21T15:00:00-05:00
2020-02-21T16:00:00-05:00
Where:
Center for Social Complexity, 3rd Floor Research Hall
Cost:
Free
Contact:
Karen Underwood
7039939298

Research Colloquium on Computational Social Science/Data Science

Scott Watson
Data Scientist
Veracity Forecasting & Analysis

Flying into the Future: Building a Career in Data Science Outside Academia

Friday, February 21, 3:00 p.m.
Center for Social Complexity
3rd Floor Research Hall

All are welcome to attend.

Abstract:
Graduation in today’s world can be a scary and disorienting prospect, as one leaves the safe confines of academia and prepares to entire an unknown world of possibilities. Questions about skills, knowledge, and capabilities can potentially become overwhelming, and the ideas about what one should do with their degree can confuse even the most prepared of us. After many years in academia, you might find yourself hesitant to try new opportunities in the private sector, believing it to be a dull and cog-like world of neckties and cubicles. This talk, however, will show how that world doesn’t have to be your reality. While the focus will be on Naval contracting viewed through my experience working for Veracity Forecasting and Analysis, the goal is to show that there are young, vibrant, growing companies that bring a different worldview to the substantive, difficult problems that face the men and women in our armed forces. I’ll show how, through the lens of data science, we can apply our knowledge and techniques to provide meaning to the unwieldy amounts of data our military has to deal with, and how we can use our skills as analysts to help them plan for the future.
Bio:
Since June 2019, Dr. Scott Watson has been a data scientist at Veracity Forecasting and Analysis, which recently became Systems Planning and Analysis, where his work focuses on the modeling and simulation of complex systems. He received his doctorate in Physics in 2018 from George Mason University while working with Kuramoto-style nonlinear networks, and has previously taught undergraduate-level courses with George Mason’s Department of Computational and Data Science.