About

Daniel Yoo is a Principal Machine Learning Engineer at Knock, where he is responsible for building state-of-the-art machine learning systems to solve complex real-world problems. With over 12 years of relevant experience, Daniel has established himself as a leading expert in the field of machine learning. Daniel's impressive track record includes being a Kaggle Master and ranking 68th out of 271,892 competitors. He also ranked 7th in the BCI Challenge @ NER 2015 on Kaggle, 17th in the Avazu Click-Through Rate Prediction challenge, and 39th of 1785 in the Higgs Boson Machine Learning Challenge. Additionally, Daniel ranked 56th of 718 in the Criteo Display Advertising Challenge. Daniel's educational background includes a Bachelor of Science in Economics from the Massachusetts Institute of Technology and a Doctor of Philosophy in Psychology from Emory University. Prior to his current role at Knock, Daniel served as the Machine Learning Lead and Senior Machine Learning Engineer at the same company. Throughout his career, he has gained expertise in a variety of tech stacks, with a particular focus on ML. Overall, Daniel is a highly skilled and accomplished machine learning engineer with a proven track record of delivering exceptional results. He is passionate about leveraging cutting-edge technology to solve complex problems and is committed to staying at the forefront of the industry.