Apple is looking to leverage data, measurement, and rigorous evaluation to drive product impact for streaming media experiences across its platforms, aiming to deliver the best audio and video experiences to hundreds of millions of users worldwide.
Requirements
- Proven track record to frame analytical questions, apply appropriate statistical techniques, and derive actionable insights from complex datasets.
- Proficiency in data querying using SQL, Spark, or equivalent technologies.
- Strong experience with a scripting language for data processing and analysis (e.g., Python, R, or Scala).
- Deep expertise in machine learning, statistical analysis, multivariate methods, A/B testing, and sampling techniques.
- Experience designing and building scalable data systems and pipelines to support complex, large-scale analytics initiatives.
- Software development experience in C, C++, Objective-C, or Swift, able to collaborate effectively with engineering teams and contribute to production-grade systems.
Responsibilities
- Collaborate closely with multi-functional teams to uncover data-driven insights and design new telemetry that measures both user experience and software performance.
- Develop innovative analytics methods to translate user experience challenges into actionable software development opportunities.
- Build robust internal tools and data pipelines to enable continuous monitoring of key metrics and KPIs across multiple applications and services.
- Partner with engineering teams to gain deep understanding of software systems and design analytics frameworks for new products and features.
- Leverage and innovate with Machine Learning and Generative AI technologies to enhance analytics capabilities, automate insights, and unlock new ways of understanding complex systems.
Other
- Excellent communication and multi-functional collaboration skills, with the ability to convey complex concepts to diverse audiences.
- Self-motivated, intellectually curious, and adept at critical thinking, with a demonstrated ability to thrive in ambiguous problem spaces.
- Master’s degree in a quantitative or technical field such as Statistics, Computer Science, Engineering, Mathematics, or a related discipline.
