Head of Analytics and Business Intelligence

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, and Instant Clusters, while supply-side economics depend on host behavior, capacity, and pricing. You will build the metric definitions, models, and self-serve layer that allow the company to reason about these dynamics consistently. Our analytics stack includes dbt and Dagster for transformation, Snowflake underneath, and Mode as our BI tool.

You will shape how Runpod uses data to make company-level decisions. You'll have the opportunity to define the metrics that matter, proactively identify business opportunities, build a scalable analytics operating model, and translate complex data into clear recommendations for executives and the board. Success means creating an analytics function that not only responds to the business, but helps lead it.

Responsibilities:

Lead, coach, and grow a team of analysts and BI practitioners, including hiring, career development, prioritization, and raising the technical bar of the work.

Drive company strategy proactively from a data perspective by identifying the data levers that can transform the business, quantifying opportunities, and delivering clear paths to action for leadership.

Own Runpod's core metric layer, defining and maintaining consistent definitions for utilization, retention, net revenue retention, margin, and marketplace supply/demand health.

Set the analytics roadmap in partnership with Product, Finance, and GTM leadership, balancing recurring reporting needs with deeper analysis that changes decisions.

Drive analysis of consumption-based revenue and customer behavior, including cohort retention, expansion and churn on usage, savings plan adoption, spot vs. reserved mix, and serverless workload economics.

Build the self-serve analytics layer so stakeholders can answer routine questions independently, reserving the team's capacity for higher-judgment work.

Partner closely with Data Engineering on modeling, data quality, freshness, and SOC 2 requirements for the analytics platform.

Establish experimentation and measurement practices, including guardrails for interpreting results.

Represent analytics in executive and board-level reporting, translating ambiguous business questions into analysis and clear recommendations.

Requirements:

8+ years of experience in analytics, business intelligence, or data science, including ownership of business-critical metrics with executive visibility.

3+ years of experience managing analytics or BI teams, with a track record of hiring, developing, and retaining strong practitioners.

Deep hands-on fluency in SQL and modern analytics engineering practices, including dbt or equivalent, with enough warehouse expertise to make sound modeling and performance trade-offs.

Experience with usage-based, consumption, or marketplace business models and the metrics that govern them, including utilization, unit economics, expansion and contraction on usage, and two-sided supply and demand dynamics.

Demonstrated ability to define a metric layer from a messy starting point and drive organization-wide adoption.

Strong judgment and urgency, with the ability to determine when a fast, directionally correct answer is more valuable than a perfect answer delivered too late.

Ability to approach questions objectively, form a view from evidence and data, and optimize for what is best for the business.