Director, Compute Finance FP&A

What You’ll Do

Own compute financial planning & Forecasting

• Build and manage consolidation models for GPU/CPU capacity, storage, networking, and data center investments.
• Translate infrastructure roadmaps into short- and long-term financial forecasts (LRP, annual planning).
• Coordinate closely with Corporate FP&A on timelines and process.
• Present insights on a monthly basis to senior management.

Drive infrastructure investment decisions

• Evaluate build vs. buy, vendor vs. owned infrastructure, and capacity allocation tradeoffs.
• Develop frameworks for investment trade-offs to guide executive decision making.

Build scalable tooling & reporting

• Implement stakeholder-facing dashboards to track compute spend, utilization, and efficiency metrics.
• Improve visibility into unit economics (e.g., cost per training run, cost per inference, cost per customer).

Drive forecasting accuracy & accountability

• Lead budget vs. actual analysis for compute and infrastructure spend.
• Identify key cost drivers (utilization, pricing, efficiency gains) and reduce forecast variance.

Support close & financial reporting

• Partner with Accounting to ensure accurate classification of infrastructure spend (OpEx vs CapEx).
• Translate complex infrastructure costs into clear insights for leadership.

Enable strategic decision-making

• Build scenario models to support leadership decisions on capacity scaling, new model launches, and infrastructure investments.
• Lead ad hoc analyses on emerging topics.

You Might Thrive in This Role If You Have

• 10+ years in strategic finance, with experience in infrastructure, cloud, hardware, or compute-intensive environments.
• 2+ years in investment banking.
• Must have experience running an FP&A team at the corporate level or business unit level with significant scale.
• Strong financial modeling skills, particularly in capacity planning, unit economics, and scenario analysis under uncertainty.
• Experience supporting large-scale infrastructure or cloud spend (e.g., AWS/GCP/Azure, GPUs, data centers).
• Ability to translate technical concepts (compute usage, model training/inference, system architecture) into financial insights.
• Proficiency in Excel/Sheets, SQL, and BI tools (e.g., Tableau); experience with planning systems like Anaplan is a plus.
• Strong cross-functional partnership skills, especially with Engineering, Product, and Supply Chain.
• Familiarity with AI/ML infrastructure cost drivers and the economics of training and serving models.