About

Christopher Riederer is a highly motivated Senior Data Scientist at Propel, Inc. He is driven by a desire to learn and is focused on producing useful results. Christopher is excited by digging into data, interesting technical challenges, and problems with a social impact. With 5.87 years of relevant experience, he has worked in several companies, including Square, where he served as a Machine Learning Engineer. At Square, Christopher used machine learning to prevent fraud at Cash App. He also improved the efficiency of Cash App's customer success organization through automation, using machine learning and natural language processing. Christopher holds a Ph.D. in Computer Science from Columbia University, where he conducted data analyses to find solutions that balance the utility of location data-based products with user privacy concerns or the possibility of algorithmic bias. Some of his notable projects include showing how large datasets of location data can be de-anonymized, inferring demographics from location data, and developing new methods of privacy-friendly and fair location-based advertising. His adviser during his Ph.D. program was Augustin Chaintreau. Christopher's tech stack includes Data Science, Research Science, Machine Learning, and Natural Language Processing. He is a highly skilled professional with a passion for using technology to solve real-world problems. Christopher's educational background includes a Bachelor of Science in Computer Science from Yale University and a Ph.D. in Computer Science from Columbia University. He also attended Rochester Lourdes High School. In summary, Christopher Riederer is a Senior Data Scientist with a passion for using technology to solve real-world problems. He has relevant experience in several companies, including Square, where he used machine learning to prevent fraud at Cash App. Christopher's educational background includes a Ph.D. in Computer Science from Columbia University and a Bachelor of Science in Computer Science from Yale University. He is highly skilled in Data Science, Research Science, Machine Learning, and Natural Language Processing.