The NYU Master of Science in Data Science is a highly-selective and extremely popular program graduating approximately 100 students a year from a two year degree. Starting in 2013, it now receives around 1700 applications per year with an acceptance rate of around 12%. The degree focuses on the development of new methods for data science, and consists of four core elements: the philosophy and scope of DS, statistics and probability, machine learning and 'big data'. Beyond this, numerous electives grouped into subject 'tracks' allow students to specialize in areas as diverse as physics, biology, mathematics and natural language processing. We also offer a large number of 'methods' courses, on deep learning, inference, algorithms, time series and other technical matters. Students are required to spend at least one full semester working on an end-to-end research project, and most do much more 'hands on' project work during their degree. Our placement rate is approximately 100%, almost all of whom go to industry. Key challenges include (a) continuing to serve students with marketable skills---both technical and 'soft'---in what is a rapidly evolving discipline and work environment; (b) incorporating ethics in a systematic way to every teaching unit; (c) hiring and retaining sufficient faculty to both run the program and provide teaching.