Simon Tidd

Simon Tidd has an extensive work experience in various roles and industries. Simon has worked as the Director of Data Science at Amida Technology Solutions since February 2024. Prior to that, they served as a Senior Data Scientist at the same company from June 2023 to February 2024. Simon also worked as a Course Instructor for a data analytics and visualization bootcamp program at edX from May 2023 to November 2023. Simon has a background in analytics and research, with previous roles including Senior Analyst at Upside, Senior Manager at Charter Communications, and Senior Research Analyst at the City of Austin. Simon also has experience in educational institutions, serving as the Director of Research and Analytic Systems Development at E3 Alliance and Manager of Program Evaluation at The University of Texas at Austin. Simon has a diverse skill set that includes data analysis, program evaluation, research, and project management.

Simon Tidd's education history includes a Ph.D. in Management (Organization Studies) and an M.A. in Sociology from Vanderbilt University, obtained from 1996 to 2001. Simon also earned a B.A. in Anthropology from Cornell University between 1988 and 1992. In terms of additional certifications, they completed a Certificate Program in Data Analytics and Visualization from the Texas McCombs School of Business in 2018-2019. Simon pursued further education in the field of machine learning, earning a MasterTrack Certificate in Machine Learning for Analytics from the University of Chicago in 2020-2021, and a Post-Graduate Certificate Program in Artificial Intelligence and Machine Learning for Business from the Texas McCombs School of Business in 2021-2022. Simon also acquired certifications in various machine learning and data analysis subjects, such as "Scalable Machine Learning with Apache Spark" from Databricks and "Apache Spark (TM) SQL for Data Analysts" from Coursera in 2023, "Machine Learning II: Advanced Techniques," "Machine Learning: Introduction to Machine Learning," "Advanced Statistical Thinking for Machine Learning," and "Statistical Thinking for Machine Learning" from the University of Chicago in 2021, as well as "Mathematics for Machine Learning: Linear Algebra" from Coursera in 2019.