Scientific discovery is a fundamental engine of human progress and economic growth, yet we lack detailed evidence on the nature of scientific work. This paper introduces the Science Task Taxonomy, a new framework that maps scientific work across 232 subfields, including both commercial and non-commercial sectors. In particular, we introduce three levels of task categories, from Level-1 tasks shared across the sciences to Level-3 tasks specific to individual subfields and sectors, with Level-2 providing an intermediate level of granularity. The taxonomy runs from 12 Level-1 task areas, such as "Analyze and model quantitative research data'', through 114 Level-2 and 2,433 Level-3 areas, down to a pool of 208,202 representative tasks, such as "Develop cell-based assays to measure pharmacodynamic biomarkers''. Using this taxonomy, we provide a systematic account of how the tasks performed by scientists differ from the tasks in the wider economy. We show that scientific work is more cognitive, requires fewer interpersonal interactions, is less manual across each of the physical, psychomotor and sensory dimensions. Science is also less codifiable, and the median scientific task takes over two hours longer to complete. We also find significant variation between scientific occupations along every dimension we measure. This paper moves the measurement of the idea production function to the task level, with important implications for our understanding of the effect of AI on science.