Alice is a data scientist at Even.com, a fintech company based in Oakland whose mission is to end the paycheck-to-paycheck cycle.
Prior to Even, Alice worked as an engineer and first data scientist at early-stage startups in the consulting, sales tech, and ad tech space. She obtained a Masters from UC Berkeley, and a Bachelor of Science from the School of Engineering and Applied Science at Columbia University.
The presentation is a case study that showcases how an algorithm widely used to generate click-through-rate (CTR) in ad tech can be used in the context of generating predictive content recommendations for salespeople. We will explore the existing approaches, the choice of approach and the problems it solves, as well as the model architecture.
I was presented with the unique opportunity to transfer my learnings in ad tech, where I developed models that enabled display side platforms (DSPs) to generate competitive bids in secondary auction systems in order to surface effective sales content recommendations for salespeople.