Senior Data Scientist, Forecasting (Integrated Planning)

CoreWeave•Sunnyvale, CA

1d•Hybrid

About The Position

CoreWeave is seeking a Sr. Data Scientist to architect our end-to-end forecasting framework. You will be responsible for advancing our forecasting capabilities across multiple time horizons—from day-ahead utilization to 5-year strategic market projections. As a lead in our forecasting processes, you will bridge the gap between technical data science and business operations, synthesizing inputs from Capacity, Sales, Product, and Finance to inform capital expenditure and infrastructure deployment.

Requirements

PhD or Master’s degree in Operations Research, Statistics, Economics, or a related quantitative field.
6+ years in demand forecasting or capacity planning, with a proven track record of managing both near-term and long-range model horizons.
Expert proficiency in Python, SQL, or other programming languages for data manipulation and predictive modeling.
Significant experience in S&OP/IBP or consensus-based planning environments.
Ability to translate complex mathematical outputs into clear, actionable strategies for non-technical stakeholders.

Nice To Haves

Experience in high-complexity, competitive, or low-margin sectors such as advanced manufacturing, semiconductors, energy, logistics, or cloud infrastructure.
Familiarity with AI infrastructure (GPUs, CPUs) and data center operational constraints.
Professional experience applying Operations Research and optimization techniques to solve supply-demand imbalances.

Responsibilities

Design and advance robust, multi-horizon forecasting processes that capture demand signals for GPU, CPU, and Storage assets across both immediate and long-range windows.
Lead the synthesis of diverse inputs including Sales and Product teams, translating market intelligence and product roadmaps into a unified, data-driven planning signal.
Serve as the forecast lead in planning cycles, working closely with Capacity Managers, Sales, Product, Finance, and Data Center Operations to ensure forecast alignment with physical constraints and financial targets.
Develop sophisticated models to interpret complex utilization data, providing the organization with a deep understanding of infrastructure consumption patterns and emerging trends.
Architect and maintain production-grade data pipelines that ensure the integrity, reproducibility, and automation of all forecasting outputs.