Research Scientist - Demand Forecasting
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Before you apply
Salary$184k – $257k
LocationMenlo Park, CA; Seattle, WA
Typefull-time
SenioritySenior
Experience6+ yrs
DepartmentInfrastructure
EquityIncluded
Company size10,000+ people
PostedSep 6, 2026 · 1mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
6+ 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
Experience with optimization solvers (Gurobi, CPLEX, Xpress, or OR-Tools) and with SQL + Python for modeling, analysis, and pipelines
Publications, patents, or recognized technical leadership in OR / optimization / forecasting
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)
Skills
SQL
Python
Gurobi
CPLEX
Xpress
OR-Tools
About the role
Meta runs a large-scale server fleet, 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 a technical owner within Server Demand Planning, you drive server demand forecasting and demand-supply matching for your area and close on feasible supply requirements: 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 long term DC & hardware infra requirements, in the right place, at the right time. You choose the right modeling approach for the problems you own, deciding when to ship a production-grade optimization system versus a fast lightweight model to unblock a decision, and you partner closely across product/service capacity owners, capacity engineering, supply chain, data center planning, and finance.
Responsibilities
•
Own and drive a multi-horizon server/MW demand forecast (near term through 2-5+ years), producing trusted, reproducible releases to inform decisions
•
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
•
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
Minimum qualifications
•
Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
•
6+ 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
•
Experience with optimization solvers (Gurobi, CPLEX, Xpress, or OR-Tools) and with SQL + Python for modeling, analysis, and pipelines
Preferred qualifications
•
Publications, patents, or recognized technical leadership in OR / optimization / forecasting
•
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)