Research Scientist, Server Demand

Meta; Bellevue, Seattle, Menlo Park (WA, WA, CA); On-site; USD 180,000 - 230,000; Full time

Job summary

Meta seeks a Senior Technical Owner of Server Demand Planning to forecast long- and near-term server capacity by rack/hardware type and region. You will build production-grade optimization models and decide when to deploy heavyweight systems versus fast prototypes, coordinating with product, capacity engineering, supply chain, data centers, and finance.

You will lead modeling approaches and ensure demand-to-supply alignment to land the right servers at the right time across Meta's global

Qualifications

• 7+ years applying operations research / management science to planning problems.
• MS in a quantitative field or equivalent experience.
• Direct experience with server/data center capacity planning at hyperscale.
• Fluency with optimization solvers and SQL + Python.

Responsibilities

• Forecast long- and near-term server capacity demand by rack/hardware type and region.
• Build operations-research models that map demand to supply for landings of servers.
• Decide when to ship production-grade optimization systems vs lightweight models.
• Serve as the connective tissue between product, capacity owners, supply chain, data centers, and finance.

Skills

Operations Research

Optimization modeling

Forecasting

Production models

SQL

Python

Time Series

Forecast Reconciliation

Hyperscale planning

Education

Bachelor's degree in CS/CE or quantitative field

MS in a quantitative field (OR/Industrial Eng/Applied Math/Stats/CS)

PhD in OR/Industrial Eng/Management Science

Tools

Gurobi

CPLEX

Xpress

OR-Tools

SQL

Python

Pandas

Job description

Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you build the operations-research models that match that demand to supply so we land the right servers, in the right place, at the right time. You set the modeling approach for the function, decide when to ship a production-grade optimization system versus a fast lightweight model to unblock a decision, and act as the connective tissue between product/service capacity owners, capacity engineering, supply chain, data center planning, and finance.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 7+ years applying operations research / management science to real planning problems in demand planning, capacity planning, supply-demand matching, network optimization, or inventory MS in a quantitative field (Operations Research, Industrial Engineering, Applied Math, Statistics, CS, or related), or equivalent experience
• Deep operations-research toolkit: mathematical optimization (LP, MILP, stochastic/robust optimization), simulation, queuing theory, and probabilistic/statistical forecasting
• Demonstrated ability to build BOTH production-grade models/systems (deployed, maintained, driving real decisions) AND lightweight/prototype models delivered fast under ambiguity
• Strong demand-to-supply matching experience: reconciling forecasted demand against constrained supply, lead times, and inventory
• Fluency with optimization solvers (Gurobi, CPLEX, Xpress, or OR-Tools) and with SQL + Python for modeling, analysis, and pipelines
• PhD in Operations Research, Industrial Engineering, Management Science, or a related quantitative field
• Direct experience with server/compute or data center capacity planning at hyperscale
• Statistical/ML forecasting depth (time series, hierarchical/probabilistic forecasting, forecast reconciliation)
• Experience with planning platforms (Kinaxis, SAP IBP, o9, Blue Yonder, Demantra, E2open) and internal capacity tools (MCP/ICPC, Capacity Explorer)
• Publications, patents, or recognized technical leadership in OR / optimization / forecasting