About Alon Kaufman

Alon Kaufman is a data scientist and has been in the industry since completing his PhD over 20 years ago. Throughout his career, the number one challenge that repeatedly came up was: how can a business derive value and insights from their data? This business challenge is especially relevant when one must combine data from multiple sources within the organization, across geographies, or even across companies. Discovering new insights by combining data sources or data from different domains served him very successfully throughout his career. For example, in the field of brain research, having the ability to combine data coming from fMRI scans with data from behavioral tests for stroke patients was key for research of rehabilitation and recovery from strokes. In the biology space, combining gene expression data with DNA knockouts helped to identify the function of specific genes; and during his time at RSA, Alon Kaufman combined data from multiple banks to build models for detecting financial fraud. All these use cases may seem wildly different, however, there was and is one common thread: the power of data collaboration. Time and again, he saw that even if you take the most sophisticated machine learning model and train it on just one data source, the resulting model will be vastly inferior to taking a very simplistic model and training it on data from multiple sources. Hence, Alon Kaufman strongly believes that any data strategy needs to have data collaboration as a key pillar.