Mitul Chowdhury
About Mitul Chowdhury
Mitul Chowdhury is an Analyst in Forecasting at Ally Financial Services, with a background in data science and education, and expertise in statistical modeling and machine learning.
Title
Mitul Chowdhury is currently serving as an Analyst specializing in Forecasting at Ally.
Current Company
Mitul Chowdhury has been working at Ally as an Analyst in Forecasting since 2016. Located at 2911 Lake Vista Dr, Lewisville, TX 75067, Ally leverages Chowdhury’s expertise in advanced statistical models and data analytics.
Education and Expertise
Mitul Chowdhury holds a Masters of Environmental Sciences from the University of Toronto, completed in 2012. He also earned a Masters of Science in Physics from Minnesota State University, Mankato in 2004, following a Bachelor of Science in the same field from the same university in 2001. Additionally, Chowdhury has a Bachelor of Science in Physics from the University of Dhaka, completed in 2000.
Professional Background
Before joining Ally, Mitul Chowdhury accumulated substantial academic and professional experience in data science and education. From 2014 to 2015, he worked as a Research Associate in Data Science at the Environmental Research Center, University of Windsor. He also served as a Research Assistant (Data Analyst) at the University of Toronto from 2011 to 2012 as well as an Assistant Professor in Science, Mathematics, and Technology Education at the University of Dhaka from 2006 to 2011. Prior to these roles, he was an Assistant Professor at American International University Bangladesh (AIUB) from 2004 to 2006 and an Instructor and Research Assistant at Minnesota State University, Mankato from 2002 to 2004.
Achievements and Projects
At Ally, Mitul Chowdhury has developed roll rate base QAT models for forecasting average delinquency and bankruptcy filings. He utilizes a variety of statistical models including ARIMA, Exponential smoothing, and Life time survival analysis for forecasting. Chowdhury collaborates with the modeling team to develop and implement new models and tools, providing insights on business issues using advanced modeling and data mining techniques. He also applies machine learning and statistical inference to enhance predictive modeling efforts.