Over the past several years, the term “Data Science” has emerged in popular media and has become a common phrase for employers and job-seekers alike. But what does it really mean and how do the practical differences between industries affect the type of work that data scientists do? Many UChicago graduate students and postdocs have quantitative skills from their training but are unsure about how it will translate beyond the academic setting. This panel will explore data-intensive roles in a diverse range of fields to illuminate a few of the options available to advanced-degree scholars.
Liz is a Senior Data Scientist on the Research and Development team at Civis Analytics. She graduated from the University of Chicago in 2017 with a doctorate in Ecology and Evolution, where she used computational methods to study food web structure. As a graduate student, she developed her software engineering skills writing packages for her own research, and studying databases and programming languages for a summer at the Recurse Center. She interned at Civis Analytics before joining the company full time, focusing on machine learning research, and developing and maintaining data science software.
Clare Huang, Data Scientist, Conversant (PhD Geophysical Sciences 2017)
Clare received her Ph.D. in Geophysical Sciences, specializing in Atmospheric Dynamics in fall 2017. She participated in the Insight Health Data Fellowship in Boston in summer 2017 and was a data science intern at the Tempus Lab working on a project related to natural language processing and information retrieval in spring, 2018. She joined the Decision Sciences team at Conversant Media in fall 2018, focusing on personalization of content delivery in digital marketing campaigns.
Mallika Thanky has been with Pulselight since 2014, with duties ranging from leading a team of healthcare fraud investigators to writing FWA-detection algorithms. She is a graduate of the University of Texas at Austin and the University of Chicago. Prior to working at Pulselight, Mallika worked at a large workers’ compensation insurance carrier where she investigated tax/insurance fraud and healthcare fraud allegations. She has extensive experience working with government agencies, solving analytics problems, conducting fraud investigations, and supporting civil and criminal litigation.
John Navarro, Senior Data Scientist, 84.51 (BA Economics 2000, MA Analytics 2018)
John Navarro is a Senior Data Scientist at 84.51° a subsidiary of The Kroger Company. He has over 17 years of experience in quantitative modeling, risk management and team leadership. When he isn’t working with data, he spends time with his three children, cooking barbecue or working out. He is currently developing an internal training course on Deep Learning in Python.