Finance Manager - AI Capacity Demand

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Financial Analysis

This role focuses on financial planning and analysis for AI capacity demand within Microsoft's Commercial Product Infrastructure (CPI) team. It involves aggregating and normalizing demand signals, identifying trends in AI usage, producing demand reports for stakeholders, and partnering with finance, capacity planning, and engineering teams to align forecasts with supply plans. The role also supports scenario modeling and improving data quality for demand forecasting processes.

What you'd actually do

  1. Aggregate and normalize demand signals across AI properties, platforms, and internal consumers
  2. Identify trends, seasonality, anomalies, and leading indicators in AI usage and capacity demand.
  3. Produce standardized demand views and reporting for LT and senior stakeholders.
  4. Translate complex demand data into clear, executive-ready insights and narratives.
  5. Support real-time or near–real-time dashboards for decision-making during capacity constraints or demand spikes.

Skills

Required

  • Master's Degree in Business Administration, Accounting, Finance, Economics, Data Science or related field OR Bachelor's Degree in Business Administration, Accounting, Finance, Economics, Data Science or related field AND 2+ years experience in financial analysis, accounting, controllership, finance, or related field OR equivalent experience.
  • Excel
  • SQL
  • Python
  • R
  • Power BI
  • analytical and quantitative skills
  • large datasets

Nice to have

  • 1–3 years of experience in analytics, forecasting, planning, or a related role (internships and rotations included).
  • Ability to clearly communicate insights to both technical and non-technical audiences.
  • Exposure to capacity demand forecasting, capacity planning, or supply/demand modeling.
  • Familiarity with cloud infrastructure, AI workloads, or GPU-based compute environments.
  • Experience building dashboards or executive-facing reporting.
  • Understanding of financial planning, cost drivers, or utilization metrics.
  • Comfort working in ambiguous, fast-moving environments.

What the JD emphasized

  • AI capacity demand
  • demand signals
  • GPU and Commercial Cloud initiatives
  • demand forecasting processes