Building a world-class data org | Jessica Lachs (VP of Analytics and Data Science at DoorDash)

Building a high-impact data organization requires a centralized model where analytics teams function as strategic business partners rather than mere service units. By aligning analytics goals with cross-functional partners, teams maintain a consistent talent bar and unified methodologies while avoiding the silos inherent in embedded structures. Effective data leadership prioritizes long-term outcomes over short-term metrics, utilizing proxy metrics to drive growth while remaining vigilant against edge cases like fraud or service failures. Success stems from a culture of extreme ownership, where data scientists proactively solve problems—even those outside their traditional scope—to drive business value. Hiring focuses on curiosity and the ability to navigate ambiguity, often favoring candidates with diverse backgrounds who can adapt to the company’s evolving needs. Leveraging AI tools further empowers non-technical teams to access data independently, freeing up resources for high-level strategic initiatives.