Hi, my name is Ben Wortman
I'm a Data Scientist!

A free alternative data API platform with ~30 data sources. Built with agentic use in mind, this leverages fastMCP, FastAPI, Postgres, and Redis, with ingestion jobs running on GitHub Actions.

An end-to-end model for the simultaneous detection and inpainting of images obstructed by fences. This was achieved by overlaying raw images with existing fence masks and training to minimize SSIM, L2, and Adversarial loss. Despite training exclusively on synthetic data, this method was able to generalize to unseen, real world data and effectively inpaint ~90% of the test images.

Through the use of NLP word embeddings from Facebook's FastText model, I was able to produce an updated emotion model which provides a 5% increase in performance using only 46% of the labels. When it comes to annotation, this increases the amount of information each label has while nearly cutting in half the costs for an equivalent dataset.

While working as an intern at Impact Radius, I matching walled garden Ad impressions to customer conversion data in order to give customers insight into how their ad campaigns were performing. To do this, I created features from browser metadata and census demographic data local to the conversion IP before using a fuzzed decision tree algorithm for classifcation. In addition to this, I also developed a preprocessing step that identified 30% fraudulent TV promo code linked conversions. When filtered out using an SVM, these dramatically improved predictive performance and the explainability of the model (shapely values).