AI Compute Capacity Analyst - Scale Data Center Ops

Fluidstack; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Fluidstack is seeking a capacity planning professional to model IT and hardware capacity across our data-center pipeline in New York. You will reconcile demand with orders, lead times, and inventory, and build automated capacity views for planning and procurement, ensuring timely energization and deployment.

The role emphasizes translating analysis into actionable decisions, automating refreshes, and leveraging data-center know-how, ERP data, SQL, Excel, and Python where applicable.

Qualifications

• Experience in capacity, demand, or supply planning for hardware-heavy operations.
• Models built in SQL or spreadsheets that withstand messy data.
• Relentless verification: numbers tie out or clear justification if not.
• Translate analysis into actionable decisions (orders, shifts, elevations).
• Automate data refreshes rather than rebuilding by hand.
• Bonus: data center or hardware supply chains, ERP data, Python, forecasting methods.

Responsibilities

• Model IT and hardware capacity across the pipeline: compute, network, and support gear needs and timing.
• Reconcile demand against orders, inventory, and lead times; flag gaps before scheduling.
• Build capacity views, planning, and procurement runs that refresh automatically.
• Chase discrepancies to ground: a miscounted rack can delay energization.

Skills

Capacity planning

Demand planning

Supply planning

Data storytelling

Process automation

Forecasting methods

Tools

SQL

Excel

Python

ERP data

Job description

Fluidstack is seeking a capacity planning professional to model IT and hardware capacity across our data-center pipeline in New York. You will reconcile demand with orders, lead times, and inventory, and build automated capacity views for planning and procurement, ensuring timely energization and deployment.

The role emphasizes translating analysis into actionable decisions, automating refreshes, and leveraging data-center know-how, ERP data, SQL, Excel, and Python where applicable.