Jeremy Toledano

I am a data scientist with 7 years of experience working across the United States, Israel, and France. My research interests lie in the fields of interpretable machine learning and tabular data learning. I have deep expertise in predictive maintenance, working with real estate data, and modeling consumer behavior.

In recent years, I co-founded Future Frame, a venture-backed startup developing transformer models to make predictions on tabular data. I led a team of data scientists at Hippo, working on risk scoring, lead scoring, and the acquisition of third-party data sources. I started my career as a research scientist at Interpretable AI, where I developed intrinsically interpretable machine learning algorithms and worked with clients in industries ranging from manufacturing to real estate and insurance.

I got my MBAn from MIT, where I studied data science, did research in natural language processing with McKinsey & Company, and organized a series of talks on artificial intelligence by senior executives. Prior to MIT, I studied applied mathematics at École Centrale Paris and physics at Lycée Louis-le-Grand.

I am passionate about history, and I was able to trace my genealogy back to 1492, when my ancestors left Toledo, Spain. I enjoy reading French literature (Albert Cohen, Karine Tuil), as well as American (Philip Roth) and Israeli (Amos Oz) novels.