Grace Wang

Grace Wang's work experience includes roles as a Data Scientist at Accion Opportunity Fund, a Quantitative Research Intern at CreditSights, and a Sole Instructor & Teaching Assistant at the University of Arizona, Eller College of Management. In their most recent role at Accion Opportunity Fund, they applied Bayesian techniques to create a predictive model for missing ethnicity and identified opportunities for business growth through impact and funnel analysis. At CreditSights, they designed and implemented models for analyzing and predicting company default risk using advanced machine learning and deep learning techniques. Additionally, they conducted research on new techniques to improve model performance. As a Sole Instructor & Teaching Assistant, they developed course materials, facilitated discussions, and received high ratings for their effectiveness. Grace also worked as an International Program Intern at Grameen Bank.

Grace Wang has a comprehensive education history. Grace obtained their Bachelor's degree in Economics from the Southwestern University of Finance and Economics in 2011, with a GPA of 90/100. Following that, they pursued a Master's degree in Econometrics and Quantitative Economics at Renmin University of China from 2011 to 2014.

Grace then continued their education at the University of Arizona, where they earned a Doctor of Philosophy (PhD) in Economics. This program lasted from 2014 to 2022. In addition to their academic achievements, Grace has also acquired various certifications in the field of Machine Learning. Grace completed several Coursera courses, including "Sequence Models", "Convolutional Neural Networks", "Machine Learning", "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization", "Neural Networks and Deep Learning", and "Structuring Machine Learning Projects". These certifications were obtained in 2019.

Currently, Grace is pursuing a Master's degree in Computer Science at the Georgia Institute of Technology. Grace began this program in 2020 and is expected to graduate in 2023.