Mingjie Zhao

Data Scientist at Wells Fargo

Ms. Zhao currently is a Data Scientist working on AI model development. Holding a M.S degree in Statistical Science from Duke University, she is very passionate about data science and artificial intelligence, and likes discussing how data science and technologies are changing our world. Ms. Zhao has over 3 years of professional experience in data analysis by articulating business questions and using mathematical techniques to arrive at a solution. Before her current job in the financial industry, Ms. Zhao has worked as a researcher in a national laboratory and a consulting firm. When she has free time, she enjoys hiking and working on data science projects to hone her skills of R and python, as well as writing DS blogs to share interesting data stories.

WATCH LIVE: February 17 @ 4:00PM – 4:30PM ET

Handling Imbalanced Classification: With Machine Learning Tactics and Business-Driven Insights

Classification with an imbalanced dataset is fairly common in the financial, insurance, and technology industries, for purposes such as identifying fraud, predicting client attrition, etc. However, handling extremely imbalanced classes in the machine learning model can be difficult. This presentation will provide insights on tactics of dealing with imbalanced dataset and will focus on two parts. The first part will discuss what kind of business information could help with the modeling, including training and evaluating the model. The other part will include techniques with the best practice of machine learning to improve model performance.