He holds a Ph.D. degree, specializing in Statistics and Mathematics, from the University of Texas at Arlington. His Ph.D. research focused on unsupervised machine learning and non-parametric statistics for Survival Data. He has previously interned at Pacific Northwest National Laboratory (PNNL), where he worked with a team of material scientists on Machine Learning models to predict the properties of metallic alloys. His work has been published in some of the top scientific journals. He was also a Data Science intern for The Hartford Insurance Group where he worked on call segmentation and bonus optimization models. He is currently working at Citibank as an AVP for the Model Risk Management (MRM) Group.

Missing Semester of Data Science

In this talk, we will look into some of the essential parts of the data science process that are rarely taught in a university course or covered in tutorials. Some of the topics we will cover are: converting a business problem into a data science problem, finding the required data, and ensuring that model performance is sustained throughout the model use lifetime.