Merchant Boost | SDSU Data Science Symposium
Merchant Boost is the live data solution provider equipping financial service companies with solutions that fill the gap between historical, real-time and live data information, to improve marketing, underwriting, and collections. We are transforming fintech with innovative payment instrument data and solutions, increasing credit access to the financially underserved, and reducing processing fees for borrowers and creditors.
OLA, underwriting, AI, ML
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SDSU Data Science Symposium

SDSU Data Science Symposium

Brookings, SD | February 4-5, 2019

The SDSU Department of Mathematics and Statistics will be hosting the annual Data Science Symposium on the SDSU campus. The symposium aims to bring together people from various backgrounds providing a mix of academic and industrial learning opportunities to gain a larger perspective of data science through connecting the education, research, and use cases in the industry.
Hundreds of industry leaders and practitioners, academic researchers, and students will be able to network and learn from each other as well as from recognized world leaders in their prospective fields.  SDSU is a leading center of research and practice of data science in areas as diverse and important as digital forensic evidence, plant genomics, consumer finance and fintech, precision agriculture, and medical research.

Merchant Boost is excited to be a sponsor of the 2019 Data Science Symposium.  Merchant Boost’s data science team is located at the Brookings Innovation Campus in order to leverage the quality of talent available.  Merchant Boost’s Chief Data Scientist, Tom Brandenburger, exemplifies this critical relationship.  In his dual role as Chief Data Scientist for Merchant Boost and SDSU Associate Professor of Mathematics and Statistics, Dr Brandenburger is providing a leadership role in development of the regional data science ecosystem. As Chair of the 2019 Symposium he has fostered the collaboration and cross pollination of methodologies and technologies of these seemingly disparate industries through the common language of data science.