Data Scientist I - Analytics & Dashboards

CoreWeave•Livingston, NJ

5d•$99,000 - $145,000•Hybrid

About The Position

CoreWeave is seeking a Data Scientist I to serve as part of the technical enablement team for the Capacity Management, Planning, and Delivery teams. In this role, you will build the analytical substrate that allows our planners to navigate the complexities of a global AI hyperscaler. You will be responsible for transforming raw telemetry from our GPU, CPU, and storage fleets into high-fidelity decision-making tools. By bridging the gap between raw data sources and operational execution, you will ensure that Capacity Planners have the real-time visibility and automated workflows required to optimize billions of dollars in infrastructure assets.

Requirements

Educational Background: Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Statistics, or Mathematics.
Technical Proficiency:
Programming: Strong proficiency in Python and SQL. Ability to write HTML for custom tool interfaces is a plus.
Modern Stack: Hands-on experience with GitHub for version control and Tableau for data visualization. Familiarity with Omni Analytics is preferred.
Development AI: Comfort using AI-augmented coding environments (e.g., Cursor) to increase output velocity.
Quantitative Foundation: Solid understanding of statistics and machine learning algorithms, with the ability to apply the right model to specific operational challenges.
Communication: Proven ability to synthesize complex data into clear, informative narratives for both technical peers and non-technical executives.
Detail Orientation: A "fanatical" approach to data integrity, ensuring every dashboard and report is verified at the most granular level.
Experience: 0–2 years of experience, including relevant internships or post-graduate work in data science, software development, or analytics.

Responsibilities

Operational Tooling & Visualization: Build and optimize sophisticated dashboards in Tableau and Omni Analytics that provide Capacity Managers with a clear view of supply-demand imbalances and hardware utilization.
Agentic Architecture: Support the build-out of autonomous AI agents by designing the underlying workflows, mapping necessary input data tables, and establishing rigorous testing protocols to ensure output accuracy.
Insight Synthesis: Programmatically extract and analyze data using SQL and Python to identify meaningful trends, translating these findings into concise, executive-level reports.
Systems Management: Maintain all analytical code within GitHub, ensuring that the tools provided to the planning team are version-controlled, scalable, and reproducible.
High-Granularity QA: Execute deep-dive audits of data pipelines and reporting outputs to guarantee the absolute accuracy of the metrics used for global capacity decisions.
Process Documentation: Create comprehensive technical documentation for all new workflows, input/output schemas, and data transformations to facilitate team-wide scalability.
Efficiency Automation: Use coding automation tools to accelerate the development of internal tools and automate manual data-gathering processes.