Business & Financial Operations Analyst - AIML
Apple Cupertino, California, United States
Computers and Electronics Manufacturing · 10,001+ employees
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About the role
The analyst will drive requisition management, quarterly fiscal planning, and vendor procurement to ensure operational rigor within the AI team. They will partner with engineering, research, and finance teams to provide insights that optimize resource allocation and support strategic decision-making.
What they look for
Requirements
Candidates must have at least 5 years of experience in business operations or financial planning within a high-tech environment and hold a bachelor's degree in an analytical discipline. Proficiency in managing the end-to-end purchase requisition lifecycle and a solid understanding of financial principles like CapEx and OpEx are required.
Full description
The SWE Ops Infrastructure & Planning team is seeking an analytical, proactive, and collaborative Business & Financial Operations Analyst to maintain operational rigor and drive standardization across the AI team within the SWE organization.
In this role, you will drive requisition management, steer quarterly fiscal planning activities, and partner closely with engineering, research, finance, EPMs, and cross-functional leadership. You will serve as a key operational partner in budget forecasting, and vendor procurement, delivering the insights, processes, and frameworks that empower leaders to optimize resource allocation, make informed decisions, and execute seamlessly against our highest priorities.
Description
The SWE Ops Infrastructure & Planning team is committed to fostering a culture of technical excellence and operational discipline. As our research and engineering initiatives grow in scale and complexity, we are looking for an analyst who thrives in bringing structure to ambiguity, connecting the bigger picture to operational execution, and bringing decision-ready insights to various levels of leadership.
The ideal candidate pairs strong project management acumen and deep analytical capability with exceptional interpersonal skills. You will drive alignment across machine learning scientists, engineering DRIs, finance, and cross-functional partners—championing clarity, accountability, and continuous improvement while ensuring disciplined stewardship of our resources through proactive forecasting and vendor management. You embody a passion to fight for excellence (striving for exceptional outcomes without settling) and the foresight to see around corners (anticipating long-term organizational, technological, and strategic trajectories).
Minimum Qualifications
5+ years of business operations, financial planning & analysis, strategy & operations experience within a high-tech or software engineering environment. Bachelor’s degree in an analytical or quantitative discipline (such as Business, Finance, Operations, Supply Chain), or equivalent practical experience. Proven track record managing the end-to-end Purchase Requisition (PR) to Purchase Order (PO) lifecycle—including vendor onboarding, scoping alignment, and proactive cross-functional chasing. Solid grasp of core financial treatment principles: CapEx vs. OpEx, prepaid assets, accruals, amortization schedules, and milestone-based billing. Demonstrated ability to track, analyze, and reconcile budget actuals vs. forecasts, identifying variances and driving corrective actions before quarter-end. Exceptional executive communication skills: ability to distill complex procurement timelines and financial figures into crisp, high-level narratives and executive summaries. Superior written and verbal communication skills, with proven ability to distill complex technical/operational information into clear, executive-ready presentations and memos.
Preferred Qualifications
CPA or MBA Experience working with data licensing, or technical vendor contracts. Direct experience partnering with or supporting Machine Learning, AI, or R&D research teams. Familiarity with data analysis, querying, and visualization tools (e.g., SQL, Excel, Tableau) to evaluate organizational metrics and build automated reporting. A natural curiosity for AI/ML technologies and how strategic investments fuel model development.
