Data Scientist, AIML Data Scientist

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 data insights that improve performance and customer experience at a global scale. Minimum Qualifications: Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. 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 Preferred Qualifications: 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 Passion for AIML and Operations, with a consistent track record of operational results.