Senior Data Scientist, CoreWeave

• Education: Master’s or PhD in Computer Science, Computer Engineering, Operations Research, or a related quantitative field
• Experience: 6+ years of professional experience in data engineering or data science, with a heavy emphasis on building production-grade planning systems (ERP, MRP, or similar operations tools)
• Software Engineering Expertise: Expert-level proficiency in Python and SQL is mandatory. Experience with modern data stack tools (e.g., dbt, Airflow, Snowflake/BigQuery) and software development best practices (version control, CI/CD)
• Systems Thinking: Proven track record of taking "weak" or unstructured data environments and scaling them into robust, automated architectures
• Attention to Detail: A fanatical focus on data accuracy and the ability to audit complex transformations for logical consistency
• This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency

Desirable

• CoreWeave is seeking a Sr. Data Scientist to architect and scale the data infrastructure that serves as the backbone of our Integrated Planning and Capacity teams
• As an AI hyperscaler, our ability to manage GPU, CPU, and storage assets in real-time is the difference between leading the market and falling behind
• Currently, our systems are in a nascent, "bare minimum" stage
• You will be responsible for leading the transition to a centralized, production-grade database system
• This is a heavy software engineering-focused role where you will build the pipelines and transformations necessary to unify disparate metrics—ranging from power utilization and node health to customer capacity allocation data—into a single, accurate source of truth
• Your work will directly enable the dashboards used by operational planners and executives, and provide the high-fidelity data required to develop autonomous, data-based agents for quantitative decision-making
• Architect Scalable Pipelines: Design, build, and maintain robust end-to-end data pipelines and transformations that aggregate data from across the organization, including data center operations, power metrics, node provisioning, and finance
• Enable Advanced Analytics: Build and optimize the data structures that power real-time and near-real-time dashboards for operational capacity and demand managers
• Support AI Agent Development: Ensure that data pipelines are architected to support the ongoing development of quantitative AI agents designed to synthesize complex data and inform high-stakes infrastructure decisions
• Cross-Functional Synthesis: Partner with Data Center Operations, Supply Chain, Product, and Finance to ensure technical pipelines accurately reflect the physical realities of data center bring-up and node health
• System Robustness: Implement rigorous testing, monitoring, and quality-control frameworks to ensure the accuracy of metrics like power utilization, storage consumption, and quality fall-out