Mathematics in Industry Careers 2019
Senior Data Scientist
YRC Worldwide, Inc, Overland Park, KS
Ph.D. 2013, Mathematics, University of Kansas
Jarod Hart received a PhD in harmonic analysis from the University of Kansas in 2013, and completed two postdoctoral appointments at Wayne State University and the University of Kansas. During his time as a graduate student and postdoc, he did research in harmonic analysis, collaborated/advised on data-driven mathematical modeling in STEM fields, and developed cognitive-based math education practices and measurements. Currently, he is a Senior Data Scientist at the trucking and logistics company YRC Worldwide. My work at YRC Worldwide involves developing and implementing mathematical models that create pricing programs, identify sales opportunities, increase operational efficiency, and improve enterprise data integrity.
Data Scientist Lead
M.S. 2009, Statistics, University of Illinois, Urbana-Champaign
Tamara Johnson is a Data Scientist Lead at Commerce Bank and has performed statistical analysis for several lines of business, including: consumer credit card, consumer deposits, commercial, and small business during her five years with the bank. She also leads a team of three data scientists and oversees the intern program in the Kansas City analytics department. She has a B.S. in Actuarial Science and an M.S. in Statistics. Prior to working at Commerce, Tamara was a research actuary at State Farm and a lecturer in the KU Math Department. Tamara has experience using predictive modeling, experimental design, unsupervised learning, forecasting, and simulation within SAS and python to find revenue generating solutions in the financial services industry.
Lawrence Livermore National Laboratory, CA
Ph.D. 2016, Computer Science, Cornell University
Colin Ponce is an applied mathematician of the Computation Mathematics Group, Center for Applied Scientific Computing at the Lawrence Livermore National Laboratory. His work is varied but generally falls under the broad umbrella of network analysis. He has previously worked on techniques for solving large network-structured linear systems and for analyzing power grid-based networks efficiently. Today much of his work focuses on developing techniques to enhance the safety and resilience of our power grids, both in the form of high-performance computing techniques for analyzing systems, and in the form of robust decentralized techniques for operational use. He also works on methods for efficiently training large neural networks.
Sandia National Laboratories, New Mexico
Ph.D. 1991, Mechanical Engineering, North Carolina State University
Jim Redmond is a Senior Manager at Sandia National Laboratories, currently leading an effort to modernize secure transportation systems. He has been with the labs for 27 years serving in a variety of roles including post-doc, staff, manager, senior manager, and acting director. In prior leadership roles he led a team to deliver the largest ever computational simulation effort at Sandia to support development and qualification of a modernized nuclear deterrent, and led a technical team supporting the Executive Vice President for National Security programs.
Among his technical contributions, Jim developed control schemes to improve precision manufacturing processes and helped establish R&D programs in Microscale Dynamics, Coupled Structural Acoustics, and Re-entry Simulation. He has served on teams supporting national emergency response efforts, including the National Transportation Safety Board I-35W Bridge Collapse Investigation, the Deepwater Horizon Accident Response, and the Waste Isolation Pilot Plant Technical Assessment Team.
Jim holds BS and MS degrees in Aerospace Engineering, and a Ph.D. in Mechanical Engineering all from North Carolina State University. He is Sandia’s Campus Executive for the University of Colorado Boulder, and serves on advisory boards for the Fort Lewis College Department of Physics and Engineering and the University of Georgia College of Engineering.
Google, San Francisco
Ph.D. 1996, Operations Research, Stanford University
Qing Wu is a Principal Economist at Google. He works on business intelligence, quantitative analysis in on-line advertising, revenue forecast and management, user/advertiser behavior modeling, and macroeconomics for Google. His specialties include internet data mining, financial forecast, macroeconomics, econometrics, supply chain and demand chain management. Qing began his career at Google in 2006 as a senior economist. He received an M.S. degree in 1991 in mathematics from the University of Kansas and his Ph.D. in 1996 in operations research from Stanford University. Before beginning his career at Google, he worked as a senior scientist at Manhattan Associates, a global solutions provider for supply chain leaders, and as a lead scientist at GAP Inc. doing data mining and analysis.