Modern data science applications frequently involve pipelines of exploratory analysis requiring accurate inference of a property of the distribution governing the data. This talk will focus on recent progress in the performance, structure, and deployment of near-minimax-optimal estimators for a large variety of properties in high-dimensional and nonparametric settings.