Responsibilities:
- Data Collection and Analysis: Collect, analyze, and interpret data from various sources and complex transactions to identify trends, and insights that inform data solutioning processes
- Data Quality Assurance: Assist in data validation efforts to ensure datasets meet end users’ requirements to deliver high quality product releases, and continuous support in monitoring data quality and resolving data discrepancies
- Collaboration: Work closely with cross-functional teams, including data engineers, business analysts and stakeholders, to gather data requirements and ensure data integrity
- Enhancements: Identify opportunities for process improvement and operational efficiency
- Research and Learning: Deeply understand Apple’s relevant business activities, commercial interests and related processes, and continuously expand your knowledge and skills in data analytics techniques and tools
Minimum Qualifications:
- 2-4 years consulting or financial/business/data analyst experience
- BS/MBA in Finance, Accounting, Economics, Business Analytics or BS/MS in STEM or quantitative field (CS, Applied Statistics, Operations Research) • Excellent problem-framing, problem solving and project management skills, with the ability to change direction quickly
- Excellent verbal and written communication skills with ability to articulate results of analysis in business terms
- Confirmed ability to conduct complex, data driven analysis
- Ability to work independently and collaboratively in a fast-paced environment
- Eagerness to learn and adapt to new tools, techniques, and technologies in the field of data analysis
Qualifications:
- Knowledge of accounting principles, financial statements, and financial modeling
- A basic understanding of data design pattern differences between transactional ERP systems (e.g. SAP) and analytical data warehouses (e.g. BigQuery, Snowflake)
- Ability to self-start and self-direct work in an unstructured environment, comfortable dealing with ambiguity
- Knowledge of SQL and working with large datasets
- Experience with data analytics tools and programming(e.g. R, Python)
- Experience building interactive data visualizations, excellent storytelling skills (e.g. Tableau, Streamlit, Shiny)
- Experience building/applying statistical and/or machine learning solutions to solve business problems
