Systems Analyst, Senior Staff - Demand Planning & Capacity Strategy

Qualcomm•San Diego, CA

9d•$140,800 - $211,200•Onsite

About The Position

At Qualcomm, the compute and storage resources that build next-generation silicon have to be planned years before the first chip is designed. Global Demand Management is the team responsible for that planning. We forecast and justify how much compute, storage, and AI capacity the engineering organization will need, when it will need it, and what it will cost, and the company commits hundreds of millions of dollars against our answer. We are hiring a senior staff demand analyst to own that forecast methodology end to end. You will translate silicon product roadmaps and tapeout schedules into multi-year demand plans, size and justify the capital purchases that meet them, and present the resulting capacity position to engineering and finance leadership. The work is quantitative, highly cross-functional, and directly visible to executives. You will also set the analytical direction for a team of analysts who build on your models, reviewing their work, raising their craft, and leaving the practice stronger and better documented than you found it. This is global planning at scale. The engineering grid spans tens of thousands of servers and hundreds of petabytes of storage across four primary data centers and roughly sixty smaller sites worldwide, supporting more than a hundred and fifty engineering teams across eleven business units. AI and GPU capacity is the fastest-growing and most contested part of that estate, and shaping how it gets allocated is a visible part of this role. The annual capital and operating plan you will help build runs into the hundreds of millions of dollars, and the planning horizon extends three or more fiscal years out. This is an office-based position located in San Diego, CA and is expected to comply with the company's onsite work policy. This is a U.S. based position and is not eligible for visa sponsorship.

Requirements

7+ years of IT-relevant work experience with a Bachelor's degree. OR 9+ years of IT-relevant work experience without a Bachelor’s degree. Completed advanced degrees in a relevant field may be substituted for up to two years (Master’s = one year, Doctorate = two years) of work experience.
Advanced Microsoft Excel, including large-scale quantitative modeling.
Demonstrated experience building business intelligence dashboards and executive reporting in Tableau, Power BI, or an equivalent platform.
Experience translating technical roadmaps or product schedules into resource, capacity, or supply plans.
Experience preparing budget or capital planning inputs and presenting them to finance partners and senior leadership.
Experience consolidating data from multiple stakeholders and sources into a single planning position, and maintaining version control over successive planning cycles.
Demonstrated experience building and delivering significant PowerPoint presentations to executive management, translating complex quantitative analysis into a clear recommendation, defending it under challenge, and driving a decision in the room.
Strong written and verbal communication, with a track record of influencing stakeholders outside your own reporting line.

Nice To Haves

Bachelor's degree in Information Systems, Engineering, Computer Science, Data Analytics, Operations Research, Business Analytics, or a related field, and seven or more years of experience in demand planning, capacity planning, forecasting, or quantitative analytics. A Master's degree in one of those fields with five or more years of that experience is equally acceptable.
Experience in semiconductor, electronic design automation, high-performance computing, or large-scale engineering environments, including familiarity with tapeout-driven demand cycles.
Experience planning GPU or AI and machine learning capacity, particularly prioritization and allocation under constrained supply.
Practical use of AI tools to accelerate analysis, modeling, reporting, or documentation. This can be learned on the job, but candidates who already work this way will have an advantage.
Familiarity with index decomposition or similar quantitative attribution methods used to explain year-over-year change in demand, cost, or consumption.
Storage capacity planning at petabyte scale, including archival, reclamation, and lifecycle management programs.
Demand or capacity planning for an acquired or newly integrated business operating outside standard corporate process.
Familiarity with high-performance computing workload schedulers such as LSF, and with grid or pool allocation models.
SQL, data modeling, and reporting automation.
Experience owning a planning or forecasting application as a product, including requirements definition and driving user adoption.
Familiarity with procurement workflows, vendor quoting, rental and interim capacity models, and capital approval processes.
Experience working with globally distributed teams across multiple time zones.

Responsibilities

Own long-range demand forecasting and capacity planning for AI systems, compute, storage, GPU, and emulation across hardware and software engineering on a rolling multi-year horizon, sizing and recommending the capacity purchases that meet it against defined deficit thresholds, and carrying each commitment from plan through quoting, approval, delivery, and installation.
Own the annual budget submission and the quarterly rolling forecast cycle with Budget Operations and Finance, including capital and operating expense framing, pricing analysis, and the written demand narrative that justifies every material change to senior leadership.
Translate product roadmaps and tapeout schedules into demand deltas and maintain strict version traceability between each roadmap release and the forecast cycle it supports, so that every budget submission reconciles to the baseline it was built on.
Attribute year-over-year demand growth to its underlying drivers using quantitative decomposition, so that capital requests are defended with measured contributions rather than narrative alone.
Consolidate demand planning for newly acquired businesses operating outside the standard process, normalizing fragmented inputs from multiple geographies into Qualcomm planning formats, validating stated capacity requirements against utilization evidence, and managing rental and interim capacity spend.
Own the forecasting methodology and the planning toolset end to end: maintain and continuously improve the models, decision rules, and utilization analytics that inform them; apply AI and automation to move forecasting beyond manual spreadsheet work; document the assumptions, thresholds, and conventions behind them; set the standards for the executive reporting built on them; serve as the escalation path across engineering, finance, data center services, operations, and procurement when capacity demands conflict; and mentor analysts so the methodology is institutionally held rather than resident in one person.