Data Scientist Capacity Planning Apple Data Platform

Help us build the capacity intelligence behind Apples next generation data and AI platforms. The Apple Data Platform organization is looking for a Data Scientist to help forecast infrastructure demand optimize capacity and improve the economics of large-scale compute will work at the intersection of data science infrastructure engineering and finance helping translate rapidly changing workload demand into actionable capacity plans and investment decisions. The role will initially focus on third-party cloud infrastructure and will expand over time to include Apple-owned is an opportunity to directly influence how Apple plans allocates and optimizes the infrastructure supporting some of its most important data and AI workloads.n

As a Data Scientist focused on Capacity Planning within the Apple Data Platform organization you will develop forecasting models analytical frameworks and data products that help teams make better infrastructure will partner closely with engineering teams to understand workload growth product roadmaps migrations performance characteristics and future infrastructure needs. You will also work with CIBO Finance Procurement and infrastructure teams to evaluate capacity strategies cloud commitments and investment initial scope will include GPUs TPUs compute storage and related resources across third-party cloud environments. Over time you will help establish a unified capacity planning framework spanning both third-party and Apple-owned infrastructure.n

Develop short- and long-range capacity forecasts for GPU TPU CPU storage and other infrastructure resources supporting large-scale data and AI demand forecasting models using historical utilization workload growth product roadmaps seasonality migrations and engineering inputs. nTranslate workload forecasts into infrastructure requirements and actionable capacity plans. nDevelop analytical models for utilization capacity efficiency supply-demand gaps and stranded capacity. nBuild infrastructure unit-economics models connecting capacity performance utilization and cost. nEvaluate trade-offs across on-demand committed reserved dedicated spot and internally owned capacity. nDevelop scenario and sensitivity analyses to understand the impact of demand uncertainty hardware changes infrastructure commitments and major platform transitions. nEstablish feedback loops and validation methods that compare forecasts with actual demand and continuously improve model accuracy. nPartner with engineering teams to understand workload behavior SLOs architecture changes and their impact on capacity requirements. nWork closely with CIBO Finance and Procurement to support infrastructure investment decisions and long-range capacity planning. nIdentify opportunities to improve utilization rebalance capacity reduce stranded resources and optimize infrastructure spend. nEstablish common metrics assumptions and forecasting methodologies across organizations. nAutomate capacity planning and reporting using data pipelines models and dashboards. nCommunicate analytical findings risks and recommendations clearly to engineering and business leaders. nHelp evolve capacity planning from reactive reporting into a forward-looking data-driven decision capability for Apple Data Platform.

3 years of experience in data science capacity planning forecasting infrastructure analytics financial modeling operations research or a related quantitative proficiency in SQL and experience analyzing large and complex datasets. nExperience developing forecasting statistical scenario-analysis or optimization models. nStrong analytical and quantitative problem-solving skills. nAbility to translate ambiguous engineering or business problems into structured analytical approaches. nExperience building dashboards metrics models or data products that support operational or investment decisions. nAbility to communicate analytical findings and recommendations clearly to technical and non-technical stakeholders. nStrong collaboration skills and experience working across engineering finance operations procurement or product organizations. nProven experience in building highly scalable compliant and secure enterprise-grade data and analytics platforms with robust data quality data governance data discovery catalog and visualization experience in leveraging data for actionable degree required in Business (with quantitative emphasis) Statistics Data Mining Machine Learning Analytics Econometrics Mathematics Operations Research Industrial Engineering or related field.n

Ability to quickly build relationships and partner cross-functionally at all levels of the organizationnFamiliarity with standard end-to-end financial processes such as forecast close analysis and reportingnSuccess leading multiple activities projects priorities and people in a dynamic fast-growing and results-driven environmentnAbility to gain an understanding of the functionality of various systemsnExperience and knowledge in SQL Python and TableaunOutstanding attention-to-detail and organizational skillsnExperience with capacity planning for GPU TPU CPU storage or other large-scale compute analyzing infrastructure capacity and cost across public cloud platforms such as AWS or GCP. nUnderstanding of AI/ML infrastructure accelerator utilization training and inference workloads and GPU/TPU capacity planning. nUnderstanding of capacity metrics such as throughput utilization efficiency latency/SLO constraints and hardware characteristics. nExperience with infrastructure unit economics total cost of ownership or cost-performance analysis. nExperience managing uncertainty across committed and elastic capacity. nExperience planning for major workload migrations or infrastructure transitions. nExperience with visualization and analytics tools such as Tableau or similar platforms. nExperience building automated forecasting or capacity-planning pipelines. nFamiliarity with Apple Silicon GPU or TPU infrastructure. nAbility to operate effectively in a fast-moving environment where demand technology and infrastructure economics are continuously evolving.