Recent technological developments related to the extraction and processing of data have given rise to widespread concerns about a reduction of privacy in the workplace. For a growing number of low-income and subordinated racial minority workforces in the United States, however, on-the-job data collection and algorithmic decision-making systems are having a much more profound yet overlooked impact: these technologies are fundamentally altering the experience of labor and undermining the possibility of economic stability and mobility through work. Drawing on a multi-year, first-of-its-kind ethnographic study of organizing on-demand workers, this Article examines the historical rupture in wage calculation, coordination, and distribution arising from the logic of informational capitalism: the use of granular data to produce unpredictable, variable, and personalized hourly pay. Rooted in worker on-the-job experiences, I construct a novel framework to understand the ascent of digitalized variable pay practices, or the transferal of price discrimination from the consumer to the labor context, what I identify as algorithmic wage discrimination.