This paper studies the implications of data technology for firm dynamics and asset prices. We develop a heterogeneous firm model in which firms optimally hire data scientists to learn about unobserved consumer preferences. Data enhances firms' demand forecasting accuracy, enabling them to charge higher markups. Firms that are constrained in expanding production capacity have stronger incentives to hire data scientists. This results in countercyclical data scientist hiring, which amplifies firms' exposure to aggregate risk via the operating leverage channel. Using a novel dataset that tracks firms' employment of data scientists, we document three key empirical findings that support the model's main mechanisms: firms with a higher share of data scientists exhibit larger markups, higher information quality, and higher stock returns.