Data Scientist, AIML Data Scientist
Seattle, WA, United States • Posted June 02, 2026
Job Type:
Full-time
Location:
Seattle, WA
Posted:
June 02, 2026
Category:
other-general
Application Deadline:
June 08, 2026
Role Description
**Weekly Hours:** 40
**Role Number:** 200647918-3337
**Summary**
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 ...
**Role Number:** 200647918-3337
**Summary**
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 ...
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