GC Sales Finance PART Analyst

Summary

At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Do you love problem solving and thinking beyond an obvious solution? Do you thrive in ambiguity and teams where little direction should fuel your creativity? The Greater China Sales Finance PART (Finance Process, Analytics, Reporting, and Technology) team is looking for a passionate and highly motivated analyst to help shape the future of finance at Apple. We support Apple's growth by applying the same level of innovation toward financial matters as we do toward our products. In this role, you will work closely with business teams to understand commercial initiatives, and partner with data engineering and data science teams to ensure our finance organization is fully empowered to operate efficiently and make well-informed decisions.

Minimum Qualifications

3–5+ years of consulting or financial/business/data analyst experience BS/MBA in Finance, Accounting, Economics, Business Analytics, or BS/MS in STEM or a quantitative field (CS, Applied Statistics, Operations Research) Excellent problem-framing, problem-solving, and project management skills, with the ability to change direction quickly Strong verbal and written communication skills with the ability to articulate results of analysis in business terms Confirmed ability to conduct complex, data-driven analysis

Preferred Qualifications

Data, Automation & Visualization: Experience with data analytics and automation platforms (e.g., Dataiku, Python, SQL) and building interactive data visualizations with strong storytelling skills (e.g., Tableau). AI Curiosity & Practice: Familiarity with AI/ML concepts and practical experience using GenAI/LLM tools to enhance daily workflows and financial reporting. Database Expertise: Knowledge of SQL and experience working with large, complex datasets. Data Architecture: A basic understanding of data design pattern differences between transactional ERP systems (e.g., SAP) and analytical data warehouses (e.g., BigQuery, Snowflake, Dremio). Finance Domain: Knowledge of accounting principles, financial statements, and financial modeling. Collaboration: User-centered delivery mindset and the ability to influence technical teams without direct authority. Adaptability: Ability to self-start and self-direct work in an unstructured environment, comfortable dealing with ambiguity.

Description

We are looking for a professional with high analytical capacity, creativity, and strong interpersonal skills to support the GC Sales Finance organization. Embedded at the intersection of finance domain expertise, product development, and program management, you will serve as a critical bridge between business stakeholders and technical teams. You will be responsible for driving the adoption, quality, and continuous improvement of next-generation analytical tools—ensuring our data landscape is well-governed and helping teams automate their daily workflows to deliver measurable value.

Responsibilities

Business & Technical Partnership: Deeply understand Apple's commercial activities and financial processes. Act as the critical bridge between GC Sales Finance and technical partners, translating complex business requirements into clear technical specifications and project plans. Process Enhancement & Automation: Partner with technical teams to design workable solutions that improve the data landscape. Explore and drive the adoption of workflow automations—using tools like Python, Dataiku, or enterprise platforms—to convert manual financial processes into scalable, repeatable data pipelines. AI Exploration & Adoption: Proactively identify opportunities to apply GenAI / LLM technologies (e.g., Copilot, Gemini) to automate reporting, enhance financial analysis, and increase overall team productivity. Data Quality & Governance: Ensure strict data accuracy across finance workflows. Partner with engineering to validate queries, enforce SQL best practices, and guide the design of reliable, user-friendly data tools. Enablement & Scaling: Train and empower analysts to fully leverage Apple's data infrastructure for building dashboards and conducting advanced analyses. Drive knowledge-sharing by creating reusable frameworks, templates, and documentation to accelerate team onboarding and solution delivery.