Senior Data Analyst
Hyperbolic is an open-access AI cloud that provides on-demand, reserved, and private GPU infrastructure for AI training, fine-tuning, inference, and production workloads. It serves startups, researchers, AI labs, enterprises, and compute providers.
Projects
About Hyperbolic
Hyperbolic operates an AI cloud platform that gives teams flexible access to high-performance GPUs through a global compute-provider network. Its offerings include self-serve on-demand GPU instances, reserved dedicated clusters, and private cloud infrastructure, supporting training, fine-tuning, inference, batch jobs, and long-running production workloads. The company serves AI-native teams, researchers, AI labs, enterprises, data centers, and infrastructure providers.
Skills
About the Role
You will establish and own the data foundation for a GPU marketplace, define and build the critical metrics that drive decisions, and deliver accurate, actionable insights to leadership. You will bridge technical AI infrastructure and business needs, develop dashboards and BI reports, ensure data correctness, and shape the analytics function as it grows.
Requirements
- 4-8 years of experience in data analytics
- Strong SQL skills
- Strong Python scripting skills
- Expertise in data debugging and ensuring data correctness
- Experience with dashboard development and BI tools such as Hex Metabase or PostHog
- Exceptional attention to detail and continuous improvement of data systems
- Strong communication and collaboration skills
- Experience working with technical teams and technical business models
- Proactive approach and comfort navigating ambiguity
- Ability to accept direct feedback and continuously improve
- Experience in GPU compute infrastructure or cloud computing (preferred)
- Background in AI infrastructure (preferred)
- Data engineering or familiarity with data pipeline development (preferred)
- Experience at high-growth early stage technical companies (preferred)
Responsibilities
- Establish and own the data foundation
- Define build and deliver critical metrics
- Transform complex data into actionable insights
- Bridge technical AI infrastructure and business needs
- Ensure data correctness and perform data debugging
- Develop dashboards and business intelligence reports
- Communicate insights clearly to leadership
- Shape and grow the data analytics function
