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.
Ali Vanderveld, Senior Data Science Lead, Amazon Web Services (Postdoctoral Fellow, Astrophysics, University of Chicago, 2010–13)
Ali Vanderveld leads a team at Amazon Web Services that builds machine learning models and systems for customers in the public sector. This includes government, education, and healthcare, and her team is specifically focused on natural language processing. Before this, Ali received a PhD in astrophysics from Cornell University and worked as a postdoctoral researcher at Caltech and then at the University of Chicago KICP. She has held a wide variety of positions throughout her Data Science career, including at Groupon, the University of Chicago Data Science for Social Good program, Civis Analytics, and most recently as the Director of Data Science at ShopRunner.
Edgar Pal, Data Scientist, Groupon (BA, 2013; MS, Computer Science, University of Chicago, 2019)
Edgar Pal is a data scientist at Groupon, working on machine learning models for pricing and promotions. He has nearly six years of data science experience, and previously held roles at Zurich Insurance and Allstate Insurance. Edgar has worked on projects related to natural language processing, experimental design, and pricing analytics. He graduated from the University of Chicago with bachelor’s degrees in economics and public policy, and a master’s degree in computer science.
Wayne Luan, Product Management (AI), Lumiata (MS, Analytics, University of Chicago, 2017)
Wayne is an analytically-driven, results-oriented strategist and operator with experience across management consulting, product management, and start-up growth advisory experience in the healthcare industry. He’s incredibly passionate about propelling the industry towards higher quality care and lowered costs by democratizing data driven solutions that lead to actionable insights and sustainable results. Wayne enjoys spending his free time traveling, cooking, and supporting mission-driven organizations. Wayne holds a B.S. in Finance from DePaul University, MSc in Analytics from the University of Chicago and is currently an MBA candidate at Northwestern University – Kellogg School of Management.
Nathan (Xiufeng) Ma, Senior Data Scientist, Octane (PhD, Geophysical Sciences, University of Chicago, 2017)
Nathan Ma has recently contributed to the exponential growth of a consumer loan portfolio as a data scientist in the credit risk team at Octane Lending. Prior to this, he did interdisciplinary research to understand the exponential growth of microbial communities in the ocean and their impact on global nutrient cycles. Ma got a PhD in Geophysical Sciences from the University of Chicago 2012-2017
Arin Greenwood, RET Design Data Scientist, Intel Corporation (PhD, Molecular Engineering, University of Chicago, 2020)
Arin Greenwood obtained her PhD in Molecular Engineering from the University of Chicago in 2020. Her research focused on computational nanoscience with applications to renewable energy devices. During her PhD, she helped solve real-world problems by creating and visualizing large simulation data sets and using statistical methods, but most of her data science skills were self-taught through classes and personal projects. She is now a Data Scientist at Intel, where she works at the intersection of data science, computational physics and engineering.
John Navarro, Lead Data Scientist, Accenture (MS, Analytics, University of Chicago, 2018)
John Navarro (BA ’00, MScA ’18) is a Lead Data Scientist at Accenture. He has over 20 years of experience in quantitative modeling, risk management and team leadership. He is also an instructor for the MScA program, lecturing Time Series Analysis and Forecasting. He is currently developing another course centered around Applied Data Science for Fintech. When he isn’t working with data, he spends time with his three sons, cooking barbecue or working out.