Saumitra Saha

Saumitra Saha has a wealth of experience in software engineering, research, and teaching. In 2022, they began working as a Software Engineer at StyleSeat. From 2017 to 2020, they worked as a Software Engineer at Programming By Induction, where they organized and supervised the moving of a flagship product from a US team to a near shore team. In 2019, they were a Software Engineer (contract) at Volley, where they redesigned a core AWS DynamoDB data model for one of the largest voice games on Alexa and Google Home. From 2009 to 2017, they were a Teaching Assistant at the University of Toronto, where they taught recitation in a highly mathematical, difficult course and improved student retention by up to 32%. From 2002 to 2009, they were a Research Associate at the Federal Reserve Bank of San Francisco, where they conducted statistical research using Machine Learning methods and represented the Federal Reserve SF to Senior, Foreign Central Bank Officials at prestigious economics conferences.

Saumitra Saha studied Economics at The London School of Economics and Political Science (LSE) from 2004 to 2005, earning a M.Sc. degree. From 1998 to 2002, they attended Northwestern University, graduating with a B.A. in Mathematics (Computer Science related). In 2008, they began a M.A. in Economics at The University of Texas at Austin, which they are currently pursuing. Additionally, they have taken courses in Computer Software Engineering at Hack Reactor. Saha holds certifications from Triplebyte as a Certified Generalist Software Engineer (obtained in August 2020), as well as several Coursera certifications, including Structuring Machine Learning Projects (obtained in January 2018), Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (obtained in December 2017), and Neural Networks and Deep Learning (obtained in November 2017).