Bio

Jennifer possesses 6+ years of professional experience utilizing data analytics for business strategy development though data manipulation and various visual storytelling techniques. She has worked in the Transportation Industry where she developed pricing strategies using various customer segmentation techniques which net over 1 million in profit. She is currently a part of the Maritz Decision Sciences Team. Here, she manages a team of analysts and data scientists. Jennifer uses various analytic methods and machine learning techniques to either develop data base architecture for building client facing dashboards or present behavioral science driven analytics/predictions to clients regarding sales performance, consumer or employee engagement metrics. Recently she and a colleague were selected to speak at the Databricks Data + AI Summit in June 2022. Here they presented their model and a dashboard Jennifer built to explain model insights to stakeholders. This passion project focused on drug addiction, particularly, predicting readmission probability. The model uses several algorithms to predict a patients outcome based on geographical, medical and other patient attributes. Jennifer created an application using PowerBi for clinician use to personalize treatment by assessing risk with a large focus on attribute contribution to prediction and feature importance.