Head of Analytics and Business Intelligence
About the role
Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform. The platform has processed more than 20 billion inference requests. We closed a $100M Series A in June 2026. We're at an inflection point for AI infrastructure, and we're building the platform the next generation of developers will depend on. Learn more in our CEO's funding announcement: https://www.runpod.io/blog/one-million-developers. We're a small, remote-first team. We take ownership seriously, move fast, and ship work that more than a million developers rely on every day. We're looking for people who care deeply, build with urgency, and want to matter at scale. Analytics at Runpod sits within Data & AI and serves as a strategic partner across the company. The team supports five core areas: marketing and PR; infrastructure and pricing; product; security; and sales. From acquisition and campaign performance to GPU-hour economics, product adoption, fraud detection, and revenue analytics, the team turns Runpod's rich operational data into decisions. This role will lead the established analytics function through its next stage of growth, determining how to staff, sequence, and scale coverage across the business while moving the team from answering questions to helping define the questions Runpod should be asking. As Head of Analytics and Business Intelligence, you will lead and grow Runpod's analytics function, owning how the company measures itself and how insights reach decision-makers. You will manage a team of analysts and BI practitioners, set the analytics roadmap, and act as the senior analytics partner to Product, Supply, Finance, Engineering, Security, and Go-to-Market leadership. Runpod's business is consumption-based and marketplace-shaped, which makes analytics genuinely complex. Demand-side revenue depends on GPU-hour utilization and workload mix across Pods, Serverless,