Recent advances in biomedicine and technology are beginning to change the priority in biomedical research towards phenotyping. The ubiquity and capability of smartphones and wearable devices to collect social, behavioral, and cognitive data can contribute to the so-called phenotyping challenge via objective measurement. This approach is applicable across various fields, but carries especially high potential in the study of central nervous system disorders. We have defined digital phenotyping as the “moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices,” in particular smartphones. As part of our efforts in this area, we have developed the open source Beiwe research platform for high-throughput smartphone-based digital phenotyping. In this talk, I will discuss the broader concept of digital phenotyping, focusing on opportunities and challenges that lie ahead. Because the main challenge in the field is arguably moving from data collection to data analysis, I believe that statisticians and data scientists are especially well positioned to tackle many of the new and exciting methodological challenges.