GRADUCon 2018 - Careers in Data Science Panel


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.


Bo Peng, Portfolio Director, IDEO (BS Mathematics 2010, MS Statistics 2012)

Bo Peng is a Portfolio Director and part of the leadership team at IDEO’s Chicago studio, where she helps clients identify and frame the right opportunities to create intelligent products, services, and systems. Previously, she was a partner at Datascope, a leading data science consultancy in Chicago, which was acquired by IDEO in 2017. At Datascope, she combined human-centered design with analytics to derive actionable business insights for clients like P&G, Motorola, and Oracle. Through Datascope’s partnership with test-prep giant, Kaplan, she helped design, launch, and teach their first-ever, 12-week Metis Data Science Bootcamp, an immersive program to help people transition into a career in data science. Bo is an active member of the local technology community, frequently speaking about applying the iterative design process to data science projects, and is the head organizer of the Data Science Chicago and the Chicago Women in Machine Learning and Data Science meetups. She has a BS in Mathematics and an MS in Statistics, both from The University of Chicago.

Liz Sander, Data Scientist, Civis Analytics (PhD Ecology & Evolution 2017)

Liz Sander is a 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 got interested in writing computational software, and developed those skills by writing packages for her own research, and by studying databases and programming languages for a summer at the Recurse Center. At Civis Analytics, she writes software to help data scientists scale up their models.

Michael Horrell, Data Science Architect, Uptake Technologies (PhD Statistics 2015)

Statistics PhD working in Chicago as a Data Science manager. First data scientist at Uptake. Saw company grow from 10 employees to around 800 and to a $2B valuation. My focus right now is on analytics for the Internet of Things. I like to indoor rock climb and run.

Matt Best, Data Scientist, Second Measure (PhD Computational Neuroscience 2016)

Matt Best recently joined Second Measure as a Data Scientist. Previously, he was a Senior Data Scientist and Manager at Allstate. There, Matt lived at the intersection of data science and behavioral science by leveraging methods from each discipline to create business value through enhancements to customer experience. He has spoken externally about ways that data scientists can use behavioral insights to become more effective. At Second Measure, he analyzes anonymized purchase data to answer real-time questions about consumer behavior. Matt graduated from the University of Chicago in 2016 with a PhD in Computational Neuroscience.


Clark Hyde, Data Scientist, Booth School of Business (Postdoc 2016)

Clark Hyde is a Data Scientist in the Information Technology department at the University of Chicago Booth School of Business. He supports Booth faculty and PhD students with research technology including high performance computing, cloud computing, code optimization, classroom tech and custom research analysis projects. He did a full career transition from engineer/biophysicist to data scientist by actively pursuing his computational interests, and also by attending a fellowship at The Data Incubator (2015), an 8-week intensive data science bootcamp geared towards PhD students. He earned his PhD in Biomedical Engineering from UCLA, and completed a postdoctoral fellowship at The University of Chicago in Biochemistry/Biophysics.