Research Scientist - Demand Forecasting

Meta•Seattle, WA

2d•$184,000 - $257,000

About The Position

As a technical owner within Server Demand Planning, the Research Scientist drives server demand forecasting and demand-supply matching for an assigned area. The role forecasts long- and near-term server capacity demand by rack and hardware type and region, and builds operations-research models to match demand to supply. The goal is to establish feasible long-term data center and hardware infrastructure requirements in the right locations and at the right times. The role selects modeling approaches based on the problem, deciding when to build a production-grade optimization system and when a fast, lightweight model is better suited to unblock a decision. It partners closely with product and service capacity owners, capacity engineering, supply chain, data center planning, and finance.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
At least 6 years applying operations research or management science to real planning problems in demand planning, capacity planning, supply-demand matching, network optimization, or inventory.
MS in a quantitative field such as Operations Research, Industrial Engineering, Applied Math, Statistics, or Computer Science, or equivalent experience.
Deep operations-research toolkit, including mathematical optimization (LP, MILP, stochastic or robust optimization), simulation, queuing theory, and probabilistic or statistical forecasting.
Demonstrated ability to build both production-grade models or systems that are deployed, maintained, and drive real decisions, and lightweight or prototype models delivered quickly under ambiguity.
Strong demand-to-supply matching experience, reconciling forecasted demand against constrained supply, lead times, and inventory.
Experience with optimization solvers such as Gurobi, CPLEX, Xpress, or OR-Tools, and with SQL and Python for modeling, analysis, and pipelines.

Nice To Haves

Statistical or machine-learning forecasting depth, including time series, hierarchical or probabilistic forecasting, and forecast reconciliation.
Publications, patents, or recognized technical leadership in operations research, optimization, or forecasting.
PhD in Operations Research, Industrial Engineering, Management Science, or a related quantitative field.
Direct experience with server or compute, or data center capacity planning at hyperscale.

Responsibilities

Own and drive a multi-horizon server and MW demand forecast, from the 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 demand-supply matching problems 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 modeling spectrum, including production-grade optimization and forecasting systems as well as prototype models and heuristics to answer leadership questions or unblock decisions.
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.