Author: Caitlin Streamer
Principal Field Data Scientist, Seattle
Caitlin has a diverse background in technology consulting, most recently as a data scientist in the natural language processing space. She approaches everything with a sharp and inquisitive mind and always loves learning about new technologies.
Using Machine Learning for Rule Building
Many of our customers use rules in their fraud workflows to identify good and bad actors. These rules, which are combinations of conditional statements that operate as data filters, can be very effective, but formulating “the right rule” can be difficult. That’s where the Ekata Field Data Science (FDS) team comes in to help customers […]