[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Meta Platforms jobs](https://jobs.opennash.com/companies/meta-platforms/) · [Search jobs](/search/) Meta Platforms · Menlo Park, CA # Research Scientist - Demand Forecasting Menlo Park, CA Research & Science Listed on Meta Platforms’s official careers site. Listed as of October 18, 2026. Check that it is still open and apply there. [Apply on Meta Platforms’s careers site →](https://www.metacareers.com/jobs/1801570277640267/) [OpenNash Jobs](https://jobs.opennash.com/) / [Meta Platforms](https://jobs.opennash.com/companies/meta-platforms/) / Research Scientist - Demand Forecasting ## 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 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 near- and long-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 release 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 IDC 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 ## 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 Experience with demand-to-supply matching: 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 - Direct experience with server/compute or data center capacity planning at hyperscale PhD in Operations Research, Industrial Engineering, Management Science, or a related quantitative field Experience with planning platforms (Kinaxis, SAP IBP, o9, Blue Yonder, Demantra, E2open) and internal capacity tools (MCP/ICPC, Capacity Explorer) Statistical/ML forecasting depth (time series, hierarchical/probabilistic forecasting, forecast reconciliation) Publications, patents, or recognized technical leadership in OR / optimization / forecasting ## At a glance - Posted by the employer: Not stated - First seen by OpenNash: Oct 11, 2026 - Last checked: Oct 18, 2026 - Listed for: 7 days - Location: Menlo Park, CA[Apply on Meta Platforms’s careers site →](https://www.metacareers.com/jobs/1801570277640267/) ## More jobs at Meta Platforms ### [AI Research Engineer](https://jobs.opennash.com/companies/meta-platforms/jobs/2ce2068cd9fcf1053dc1/) Menlo Park, CA ### [AI Research Manager - Meta Superintelligence Labs](https://jobs.opennash.com/companies/meta-platforms/jobs/2b9038fb99fde6a938ed/) Menlo Park, CA ### [AI Research Scientist - MSL FAIR Foundations](https://jobs.opennash.com/companies/meta-platforms/jobs/d18ce9293309ea34ebd4/) Menlo Park, CA ### [AI Research Scientist - Meta Superintelligence Labs (Technical Leadership)](https://jobs.opennash.com/companies/meta-platforms/jobs/44ab514fe53310304599/) Menlo Park, CA ### [AI Research Scientist, AI Safety and Security](https://jobs.opennash.com/companies/meta-platforms/jobs/c4a620c30eddb9df62ec/) Menlo Park, CA ## Similar jobs at other companies ### [Research Data Scientist, Cloud Demand Forecasting and Capacity Planning](https://jobs.opennash.com/companies/alphabet/jobs/7fddfca6f09cbea95f87/) Alphabet · Atlanta, GA, USA +1 more ### [Senior Data Scientist - Demand Planning and Forecasting](https://jobs.opennash.com/companies/oracle/jobs/71e58b51b1e2e885cca8/) Oracle · Nashville, TN, United States ### [principal data scientist, Supply Chain Forecasting & Optimization](https://jobs.opennash.com/companies/starbucks/jobs/2b885b979a4d4fbf65f0/) Starbucks · Seattle, Washington, United States ### [Research Scientist 2](https://jobs.opennash.com/companies/humana/jobs/ec75b9eedca849c2c7ce/) Humana · Remote, Nationwide ### [Senior Research Scientist - Bioanalytical LCMS Research and Development](https://jobs.opennash.com/companies/thermo-fisher-scientific/jobs/e9e321eedbccee5ebefa/) Thermo Fisher Scientific · Richmond, Virginia, United States of America OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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