Research Scientist, Server Demand Forecasting

Meta; Menlo Park (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Meta is seeking a senior leader to own the multi-horizon server and MW demand forecast for Infrastructure. You will drive production-grade optimization and forecasting systems, aligning demand with hardware roadmaps, cooling, and power constraints to inform the Plan of Record.

You will mentor senior ICs, collaborate with data center engineering and capacity teams, and set standards for forecast-to-actual performance.

Qualifications

• Bachelor's degree in CS/engineering or equivalent practical experience.
• 8+ years applying operations research to planning problems in demand/capacity
• MS in quantitative field or PhD preferred; advanced forecasting depth.
• Deep optimization, simulation, queuing theory, and forecasting methods.
• Proven production-grade models and lightweight prototypes.
• Experience reconciling forecasted demand with constrained supply and lead times.
• Strong SQL and Python for modeling and pipelines.
• Familiarity with planning platforms and internal capacity tools.

Responsibilities

• Own multi-horizon server and MW demand forecast (2-5+ years) by resource/type and region.
• Aggregate and normalize signals into a single long-term demand plan.
• Formulate and solve demand-supply matching with OR models considering roadmaps, cooling, lead times, power.
• Build production-grade optimization and forecasting systems plus prototypes.
• Define operating model, track forecast accuracy, and close gaps to actuals.
• Collaborate with data center engineering and hardware strategy to align capacity plans.
• Set multi-year strategy across Infrastructure orgs and mentor senior ICs.

Education

Bachelor's degree in CS/Engineering/related field

MS in Operations Research/Industrial Engineering/Applied Math/Statistics

PhD in OR/Industrial Engineering/Management Science or related

Time-series forecasting

Forecast reconciliation

Optimization/OR toolkit experience

Production-grade modeling and systems

Server/data center capacity planning

Tools

Gurobi

CPLEX

Xpress

OR-Tools

SQL

Python

Kinaxis

SAP IBP

o9

Blue Yonder

Demantra

E2open

Job description

About

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 principal technical leader for Server Demand Planning across Infrastructure, you own the demand side of the plan and the feasible supply requirements it drives: 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 Meta's technical approach to server demand planning, decide when to ship a production-grade optimization system versus a fast lightweight model to unblock a decision, and set direction across product/service capacity owners, capacity engineering, supply chain, data center planning, and finance, partnering directly with org leaders and growing the technical bench behind you.

Responsibilities

• Own the multi-horizon server/MW demand forecast long range (2-5+ years), by resource type and region, and the DC supply requirements it drives
• Aggregate and normalize demand signals from short term demand and product groups, into a single trusted statistical long term demand plan
• Formulate and solve the demand-supply matching problem using operations-research models that reconcile forecasted demand with hardware roadmaps, cooling, lead times, and power constraints to inform the Plan of Record
• Build across the full modeling spectrum: production-grade optimization and forecasting systems and prototype models and heuristics that answer a leadership question or unblock a decision
• Set functional standards: define the operating model, bridge short- and long-term forecasts, track accuracy and supply-matching metrics, and close forecast-to-actual gaps
• Partner with data center engineering, site selection, and hardware strategy teams to align next-generation data center designs, rack sizing, and hardware roadmaps with demand, eliminating stranded power, cooling, and space capacity
• Set the multi-year demand-planning and supply-matching strategy across Infrastructure orgs, spotting capacity risks and opportunities years out and steering decisions before they are expensive to reverse
• Grow the technical bench: mentor senior ICs across the planning org and raise the modeling bar company-wide

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 8+ 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
• Experience reconciling forecasted demand against constrained supply, lead times, and inventory in a planning or capacity environment: 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 Experience with planning platforms (Kinaxis, SAP IBP, o9, Blue Yonder, Demantra, E2open) and internal capacity tools (internal capacity planning and supply-matching tools)
• PhD in Operations Research, Industrial Engineering, Management Science, or a related quantitative field
• Statistical/ML forecasting depth (time series, hierarchical/probabilistic forecasting, forecast reconciliation)
• Direct experience with server/compute or data center capacity planning at hyperscale
• Publications, patents, or recognized technical leadership in OR / optimization / forecasting