Senior Data Scientist - Special Projects

Apple’s intelligent systems generate rich, multi-modal data from devices, sensors, software, and services. We’re looking for a data scientist who can bring clarity to this complexity — someone who can analyze diverse datasets, surface meaningful insights, and design intuitive tools that help teams understand and improve the intelligence behind Apple products. You’ll work across the full data lifecycle: discovering signals in large-scale distributed logs, building search and retrieval mechanisms to make data accessible, and crafting interactive visualizations and evaluations that guide product direction and system performance.

Description

Our team works at the intersection of hardware, software, and intelligence. We design the systems, infrastructure, and tools that enable Apple’s next generation of AI-driven experiences — from on-device middleware and distributed inference platforms to large-scale data pipelines, interactive analytics, and advanced developer tooling. We collaborate closely with hardware, robotics, ML, design, and platform teams to build end-to-end solutions that are performant, intuitive, and deeply integrated into Apple’s ecosystem. The work is hands-on, highly cross-disciplinary, and central to shaping how Apple’s intelligent systems evolve.

Minimum Qualifications

Proven experience in data science, analytics engineering, or applied research roles
Strong proficiency in Python and common data analysis libraries
Expertise with data visualization tools or frameworks for building interactive dashboards
Experience querying and modeling data in SQL and NoSQL environments
Ability to analyze large-scale, high-dimensional, and multi-modal datasets
Familiarity with designing or using search and retrieval systems for large-scale data
Experience designing KPIs, evaluation metrics, or experiment analyses for complex systems
Strong statistical intuition and experience with exploratory data analysis and hypothesis testing
Ability to translate complex findings into clear, actionable insights for cross-functional teams
Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or related field, and 5+ years of industry experience

Preferred Qualifications

Experience working with data from distributed or real-time systems, robotics, or multi-modal AI
Familiarity with information retrieval techniques (ranking, embedding-based search, relevance modeling)
Experience collaborating with ML teams on evaluation methodologies, dataset design, or model diagnostics
Knowledge of metadata management systems, cataloging approaches, or data documentation strategies
Background in statistical modeling, time-series analysis, or anomaly detection
Experience with visualization frameworks used for large datasets
Understanding of cloud-scale data processing and distributed compute frameworks