Senior Data Scientist, Forecasting (integrated Planning)

Weights & Biases Weights & Biases · Data AI · Bellevue, WA +2 · Supply Chain & Capacity Operations - G&A

This role focuses on architecting and advancing an end-to-end forecasting framework for GPU, CPU, and Storage assets, bridging technical data science with business operations. It involves designing multi-horizon forecasting processes, synthesizing diverse inputs, developing sophisticated models for utilization data, and maintaining production-grade data pipelines. The role requires expertise in Python, SQL, and demand forecasting/capacity planning.

What you'd actually do

  1. 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.
  2. lead the synthesis of diverse inputs including Sales and Product teams, translating market intelligence and product roadmaps into a unified, data-driven planning signal.
  3. 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.
  4. develop sophisticated models to interpret complex utilization data, providing the organization with a deep understanding of infrastructure consumption patterns and emerging trends, while architecting and maintaining production-grade data pipelines that ensure the integrity, reproducibility, and automation of all forecasting outputs.

Skills

Required

  • PhD or Master’s degree in Operations Research, Statistics, Economics, or a related quantitative field
  • 6+ years in demand forecasting or capacity planning
  • 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 have

  • 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

What the JD emphasized

  • proven track record of managing both near-term and long-range model horizons
  • Expert proficiency in Python, SQL
  • Significant experience in S&OP/IBP or consensus-based planning environments