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Senior Data Scientist - Special Projects

LinkedIn Apple Cupertino, CA
Not Applicable Posted March 14, 2026 Job link
Responsibilities

On the data-focused role at Apple in Cupertino, you'll explore and model large-scale multi-modal data, design dashboards and visualizations, and develop search and indexing strategies to make data discoverable and actionable. You will partner with AI, robotics, hardware, UX, and cloud engineering teams to define evaluation frameworks, KPIs, data organization, and validation strategies, improving data quality, collection, and pipelines. You will also interpret data in the broader system context and communicate insights clearly through analyses, visual storytelling, and stakeholder presentations.

Commitments

Apple accepts applications to this posting on an ongoing basis.

Not Met Priorities
What still needs stronger evidence
Requirements
  • 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
Preferred Skills
  • 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
Education
  • (Not required) – Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or related field, and 5+ years of industry experience