SAS | The Power to Know
Clark Bradley

Clark Bradley
Solutions Architect, SAS  

Bradley provides field enablement and sales support leadership to SAS field teams in the areas of data management, data integration and data quality in big data environments. His responsibilities include analyzing data architecture, analyzing complex SQL and investigating Hadoop technologies, as well as system and subsystem tuning across SMP and MPP platforms.

Scott Chastain

Scott Chastain
Senior Manager, SAS Data and Decision Engineering Practice

Scott Chastain’s goal is to drive more value from data. He believes that organizations should balance governance and agility when it comes to big data architectures and programs. From high-velocity event streams to massive Hadoop clusters, Chastain advocates taking analytics to where data lives to make a greater impact and gain competitive advantage.

An engineer by education, Chastain works with customers to address the people, process and technology aspects of big data challenges. Chastain is currently responsible for leading several key domains, including data management, business visualization and decision management.

Brian Garrett

Brian Garrett
Principal Solutions Architect, SAS

With more than 20 years in analytics and IT architecture, Garrett has worked on big data projects around the world, including the 2010 US census. Prior to joining SAS, he was the Chief Technical Officer of Mustard Tree Instruments, where he developed an analytical and computing platform for the pharmaceutical and chemical industries. Garrett holds a bachelor’s in statistics from North Carolina State University and a master’s in information systems from The George Washington University.

Rachel Hawley

Rachel Hawley
Analytics Solutions Architect, SAS  

Rachel Hawley assists customers in defining their business problems and objectives, and using SAS advanced analytics solutions to help them reach their goals. Her main focuses are SAS In-Memory Analytics solutions and SAS Decision Management. Hawley holds a bachelor’s in mathematics from the University of Rochester and a master’s in operations research from North Carolina State University.

James Kochuba

James Kochuba
Senior Solutions Architect, SAS Enterprise Architecture Practice

James Kochuba helps SAS customers design and build high-performance architectures. Kochuba focuses on cloud computing and software virtualization. Prior to SAS, he worked at IBM in architecture, development and support roles. His goals are to help organizations modernize their architectures to turn data into information, visualize information for insight, and make better decisions.

Adam Pitz

Adam Pilz
Solutions Architect, Americas Analytics Practice, SAS
Adam Pilz applies data science techniques to acquire, manipulate, and model data using SAS advanced analytics technologies. He holds a master’s degree in economics from The Ohio State University and a master’s degree in analytics from the Institute for Advanced Analytics at North Carolina State University.

Catherine Truxillo

Cat Truxillo
Senior Manager, Advanced Analytical Education, SAS

Catherine Truxillo manages a team of statisticians, predictive modelers, and data scientists who support SAS advanced analytics training worldwide. Her department's clients come from many industries, including insurance, finance, manufacturing, pharmaceuticals, behavioral research, marketing, education and retail. She has written or co-written courses for multivariate statistics, linear and generalized linear mixed models, structural equation models, statistical process control, advanced business analytics, data science, predictive modeling and cluster analysis. Truxillo is an INFORMS Certified Analytics Professional and a SAS Certified Statistical Business Analyst.

Chip Wells

Chip Wells
Senior Analytical Consultant, SAS

Chip Wells has over 15 years of experience in implementing theoretical and applied econometrics using the SAS programming language and SAS Solutions. He is a Statistical Services Specialist in the SAS Education Division, where he instructs and consults with analysts from the federal government and the chemical, energy, financial, health care and transportation industries.

He was previously a Principal Analytic Consultant in the SAS Advanced Analytics Lab, where he developed solutions that focus on time series analysis of financial variables and on building forecast models using sentiment data.

Terry Woodfield

Terry Woodfield
Principal Analytical Consultant, SAS

Terry Woodfield’s primary technical expertise is in time series forecasting, predictive modeling and text mining. He began coding text mining algorithms 20 years ago to improve lift for fraud models in insurance. He has applied advanced analytical modeling strategies to problems in insurance; health care; gaming and hospitality; energy; and other areas. Since 1999, Woodfield has trained and mentored SAS customers to promote the use of analytics to solve business problems. He also develops course material for forecasting, text mining and fraud modeling. Woodfield holds a PhD in statistics from Texas A&M University.

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