- Data science lead for the Picture Proof of Delivery computer vision image recognition pipeline; a deep learning model that automatically classifies the image quality of every delivery image taken by FedEx employees. The cloud-based model labels over 5 million images each day and can determine poor quality image capture procedures such as packages not being visible in the photo or photos that contain sensitive information. This lead development role includes the training of other data scientists, leading new developments of the system, and presenting to business partners.

Created advanced data solutions for FedEx Ground and FedEx Dataworks. (Machine learning, SQL, forecasting, python automation, production-level dashboards, shell scripting, Google Cloud Platform (GCP), data engineering, model creation, and advanced cloud functions such as Vertex AI, Compute Engine, Vision AI)Notable Projects:- Multi-level, cloud based, computer vision deep learning pipelines for picture proof of delivery and package signature quality- Signature optical character recognition- Multiple production-level package status code dashboards and automated alerting systems- Managed multiple automated data ingestions- Package security and safety machine learning engineering- Package delivery quality algorithm that calculates a score for every FedEx delivery- Package handler injury forecasting models

- Provided recommendations, python code implementation, and constructed scripts to determine the accuracy of the prediction model for improvement of the predictive algorithm to be delivered to the company’s Senior Analysts and Consumer Insights Team- Applied analytical methods to discover insights regarding a new-clothing item sales prediction algorithm, working directly in the company’s AWS systems using Python and SQL