In this work, we take a network science approach to studying large-scale intrinsic brain networks during three important periods of development. In the first study, we employ sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 (n = 92). We demonstrate that age is positively associated with network segregation at multiple spatial scales, and that associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, at two ends of a gradient from perceptual, externally-oriented cortex to abstract, internally-oriented cortex. In the second study, we uncover the community structure of cortex in children aged 9 to 11 years (n = 670). We show that children have similar community structure to adults in early-developing sensory and motor communities, but differences emerge in association areas. Children have more cortical territory in the limbic community, which is involved in emotion processing, than adults. Regions in association cortex interact more flexibly across communities, perhaps reflecting cortical boundaries that are not yet solidified, and uncertainty is highest for cingulo-opercular areas involved in flexible deployment of cognitive control. In the third study, we map the associations between neighborhood SES and functional brain networks in a sample of children between the ages of 8 and 22 years (n = 1012). We characterize network topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High- SES youth show stronger positive associations between age and segregation than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. Collectively, our results provide new insights into how changes in cortical organization give rise to changes in the mind as children grow up, and how variation in the neighborhood environment might in turn affect brain development.