Senior Data Scientist, AIML Data Operations
Operations, Data Science
Cupertino, CA, USA
USD 175,500-263,800 / year + Equity
Posted on Jul 25, 2026
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. We are currently seeking an experienced Senior Data Scientist to support the AIML Data Operations Annotations Analytics team. This position will lead the development of scalable data science, data engineering, metrics, and reporting capabilities that measure and improve the health, productivity, quality, and performance of AIML Data Operations. This position will strategize and partner successfully to deliver complex cross-functional projects, generate actionable insights, and apply experimentation, automation, and emerging technologies to optimize workflows, strengthen decision-making, and enhance the analyst and customer experience.
The ideal candidate for this role is an experienced data scientist with deep expertise in analytics and experimentation, excels at building strong cross-functional relationships to drive data-informed decisions across the company, and is skilled at surfacing and communicating key data insights that improve performance and customer experience at a global scale.
- As the member of the Data Operations Capacity Planning & Analytics team, you will:
- Establish a Data Science center of excellence for AIML Data Operations by partnering across customer groups and Operations teams to uncover actionable insights and promote consistent analytical best practices.
- Develop scalable metrics frameworks, data pipelines, operational datasets, and reporting systems that accurately measure business health, project performance, productivity, and quality.
- Establish, enhance, and socialize key operational metrics while leading proactive analyses to identify performance drivers and recommend improvements.
- Build self-service dashboards and reporting tools that empower stakeholders to monitor performance, evaluate trends, and make data-informed operational decisions.
- Draft data schemas, instrumentation requirements, and engineering specifications that enrich operational datasets and support new projects, analyses, and measurement capabilities.
- Oversee large, complex projects from conception through completion by defining roadmaps and requirements, managing risks and contingency plans, evaluating impact, and communicating progress to executives.
- Analyze annotator behavior, task complexity, and data characteristics to improve project scoping, workflow design, guideline development, capacity forecasting, and the overall analyst experience.
- Apply experimentation, automation, Generative AI, and emerging technologies to optimize project structures, streamline Data Science and annotation workflows, and scale operational impact.
- Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field.
- 4+ years of experience in managing data science, analytics, or data operations teams
- 4+ years of experience in data science with proven skills in developing meaningful and concise analytic objectives from general business goals
- Tested capabilities and comfort in scalable schema designs, relational database and big data technologies, ETL, code management, and query performance optimization
- Mastery in SQL-based languages, and proficiency in at least one large-scale data languages
- Strong hands-on experience interpretable with machine learning models and sophisticated analytic solutions using scripting tools such as Python or R
- Masters degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics or related field.
- Experience with the deployment of Large Language Models / Generative AI in service of efficiency in operations
- Excellent communication and presentation skills with meticulous attention to detail and the ability to collaborate effectively between business and analytic teams at multiple levels of the organization
- Experience in managing data science or analytics teams in AI & ML annotations and collections areas.
- Passion for AIML and Operations, with a consistent track record of operational results.