ML Data Science Manager, ISE Analytics and User Studies

As the manager of the ISE Data Science team, you will lead and mentor a talented group of data scientists to understand customer engagement with Apple’s products and features. You will oversee the team’s efforts to collect, analyze, and interpret vast amounts of quantitative (telemetry) and qualitative (customer feedback) data to help improve Apple's products, inform strategic directions, and enhance the overall user experience. You will work closely with the Input Experience Analytics software engineering team to design and implement metrics for our software features, as well as the ISE User Studies team to establish a holistic picture of the user experience. The ideal candidate for this role is an experienced manager 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 leading teams to surface and communicate key data insights that improve performance and customer experience at a global scale. Minimum Qualifications 2+ years of experience managing or leading diverse teams of data scientists and/or software engineers and researchers Can lead teams in applying statistical analysis and inference, A/B experimentation and modeling (e.g. statistical, machine learning), to drive data-informed decisions, while maintaining hands-on proficiency in Python, SQL and Tableau Able to translate complex data into clear, actionable insights and recommendations for executive leadership and cross-functional stakeholders, ensuring alignment between technical findings and business objectives Organized, highly attentive to detail, and adaptable to rapidly changing requirements and environments Preferred Qualifications 5+ years of management experience Experience working on consumer-facing products or shipping products Experience using AI tools for text or image creation and editing (e.g. ChatGPT, Gemini, Apple Intelligence), and/or AI models for data analysis, synthesis, or evaluation workflows Advanced degree in data science, engineering, or any related field of study