Data Scientist, AIML Data Scientist

Benefits

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Not verified last checked Jun 13, 2026

Salary

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401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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About this role

Data Scientist, AIML Data Scientist Cupertino, United States of America Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you love thinking analytically? Are you passionate about solving complex business problems in a fast-paced environment? The AIML Data Operations group engages with teams across Apple's ecosystem with the ultimate goal of delivering high-quality annotated data in support of unreleased products and ground breaking AI technology. Within the Data Operations organization, the Capacity Planning & Analytics team provides forecasting, capacity planning and optimization, data products, metrics reporting, modeling & experimentation, and ad hoc analyses. We are seeking a highly motivated Senior Data Scientist to lead analysis into annotation project trends to uncover patterns in annotator performance, task complexity, and data characteristics to help optimize task design. You will translate behavioral insights and empirical findings into optimized project structures and workflows, and power capacity planning & optimization with quantitative rigor-all to ensure we consistently launch projects that are smarter in design, faster in execution, and uncompromising in quality. You will partner closely with Data Ops Client Engagement, Human Factors engineering and annotation customers to collaborate on the most effective methods. The ideal candidate for this role is an experienced data scientist with deep expertise in analytics and experimentation, who excels at building strong cross-functional relationships to drive data-informed decisions across the company, and is skilled at partnering with operations and engineering teams to surface and communicate key

Read the full description at jobs.apple.com. FewerJobs shows a source-linked preview and links to the original posting.