Inside Data Science

Data scientists appeared suddenly in the early 2010s and quickly became ubiquitous. Institutions, from established corporations to start-ups, universities to government agencies, scrambled to recruit specialists. Somehow, a loose band of computer experts and hackers integrated established technologies and methodologies—and some questionable ideas—into a distinct profession. Where did data science come from, and why did it gain broad recognition?

Inside Data Science examines how data scientists defined their professional role and identity, offering an empirically rich and theoretically grounded account of the emergence of a new field. Philipp Brandt met data science’s early protagonists in New York City’s start-up spaces, coffee shops, and lecture halls, where they displayed a puzzling combination of enthusiasm and uncertainty. At these seemingly casual gatherings, data scientists devised the machinery for seeing the world through datasets while also analyzing the social context of their technical work. Retracing their conversations, Brandt demonstrates how the data scientist role emerged from the collective processing of personal struggles navigating the uncharted space between statistical expertise and coding skills. Offering a novel analytical lens and critical perspective on data science, this book shows how the interplay of personal reflection, technical rigor, and collective scrutiny gave the big-data era, for better or for worse, a human face.

Before becoming a global phenomenon, data science took shape through uncertainty and collective curiosity. Blending ethnography, personal practice, and historical insight, Brandt offers an indispensable, must-read account of its rise through meetups and job boards, showing how shared technical experimentation forged data science into the transformative profession it is today. --- This brilliant ethnography captures the emergence of data science. In a theoretically and methodologically sophisticated analysis, it reveals how scattered data hackers constructed an identity as data scientists through reflexive storytelling. This is a must-read that greatly advances our understanding of expertise formation and the emergence of professions.