ASK THE EXPERT WEBINAR SERIES

SAS Models Around the World

Wednesday, 26 February • 8:30 a.m. IST • 11 a.m. SGT • 2 p.m. AEDT • Cost: Complimentary

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About the webinar

SAS models provide a tangible path to infuse AI, machine learning and analytics modernisation across industries in unique and effective ways. They allow organisations to leverage lightweight, scalable capabilities that enhance organisational AI maturity models by embedding proven elements where and when they are needed.

Among other responsibilities, SAS’ AI and machine learning division is tasked with hardening field service expertise into a software product. Join Artin and Sanjay as they share insights from the journey to garner that expertise, as well as developing software that solves customers’ business problems.

Why attend?

  • Hear about the value of SAS models.
  • Learn about SAS models currently available.
  • Discover some of the planned SAS models.

Don’t miss this opportunity to gain valuable insights into the development of AI-driven solutions and learn how SAS models can help your organisation achieve its goals.

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About the experts


Artin Armagan

Senior Manager, Applied AI and Modeling, SAS

Artin Armagan is a statistician working with a brilliant team of data scientists building real-time transactional fraud detection models for financial institutions. He has worked on analytical modeling across various business domains, including banking, insurance and health care, throughout his tenure at SAS. Previously, he held postdoctoral positions at Duke University following the completion of his graduate studies at the University of Tennessee.


Sanjay Arangala

Senior Manager, Applied AI and Modeling, SAS

Sanjay Arangala has decades of analytical experience across a variety of industries and specializations. For the majority of the last 15 years, he has led a team of analytical consultants and data scientists solving customer business problems with predictive analytics, network analysis and text-based analyses for banks, insurers and government agencies.

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