Data Scientist with extensive experience in statistical modeling, machine learning, and dashboard development, focusing on the credit and collections sector. Specializes in developing scoring models and customer clustering and classification techniques to estimate credit risk and delinquency. Proficiency in creating simulations to analyze customer portfolio profitability and devising models for optimizing email communication conversion.

Notable achievements include constructing convolutional neural networks for image identification utilizing TensorFlow and Keras, and developing a classification model using neural networks. Successfully increased email communication conversion by 12% through the implementation of a LightGBM classification model. Enhanced debt collection performance by 10% with logistic regression models using Sci-Kit Learn. Additionally, contributed to the development of an internal library of functions to improve model infrastructure, available for use by various teams within the organization.