Senior Product Data Scientist

Summary

Would you like to drive the future of Apple’s products, applications, and platform while having the unique opportunity to impact some of the most far-reaching software in the world? The Apple Services Engineering (ASE) organization leads the development and innovation on Apple’s cloud-centric products and experiences for users all over the world, including iCloud+, Photos, Mail, Messages, FaceTime, Calendar, Notes, etc. We are the foundation on which Apple’s software developers build the products that our customers love. Our multi-disciplinary data team plays a fundamental role in this mission by partnering closely with product, engineering, and business teams to develop a culture of leveraging data to inform and craft our strategy.

Minimum Qualifications

8+ years in a data analytics or data science role (6+ years in a data science role). You have excellent verbal and written communication skills and experience communicating technical concepts to senior executive audiences in order to influence decisions with data. You have proven experience in SQL and at least one programming language (e.g., Python, R) and are comfortable developing code in a team environment (e.g., git, notebooks, testing). You think about data in terms of statistical distributions and have a big enough analytics toolbox to know how to find patterns in data, identify targets for performance, and identify sources of variance about those targets. You use good judgment balancing art and science when visually communicating information using state-of-the-art visualization tools You have engineered information out of massive and complex datasets, e.g., Spark. You are self-motivated and curious with proven creative and critical thinking capabilities and a highly developed aim to improve how things work. You have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.

Preferred Qualifications

Advanced degree (Master's or PhD) in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, or Physics. Deep, hands-on experience designing and evaluating experiments beyond standard A/B tests, e.g., causal inference, quasi-experimental methods, or Bayesian approaches — when a clean randomized test isn't available. Strong product sense and a passion for building great in-app experiences. You've used data to shape apps, user journeys, and engagement, and care about translating analysis into friction-free, delightful outcomes for users. Experience working with consumer product data at massive scale, and comfortable with the engineering tradeoffs that come with it (sampling, latency, cost). A track record of mentoring or leading other data scientists/analysts, and raising the technical bar of a team.

Description

As a Senior Product Data Scientist on iCloud's data team, you'll turn complex product and behavioral data into a clear narrative that shapes how ASE builds iCloud+, Photos, Mail, Messages, FaceTime, Calendar, and Notes. You'll partner directly with product, engineering, and business leaders to define the metrics and experiments that measure our impact, then translate that analysis into insights senior leadership can act on. This is a high-visibility role for someone who's energized by ambiguity and wants their work to directly move product strategy. We are looking for someone with a track record in identifying, executing, distilling and communicating technical projects to senior leadership, leading to better, more data-informed decision-making.

Responsibilities

Design and analyze A/B tests and experiments to evaluate the impact of product changes across hundreds of millions of iCloud users. Translate complex data into a clear narrative for senior leadership, surfacing key insights and recommended actions. Partner with Data Engineering and product teams to define success metrics and the instrumentation needed to measure them. Build forecasting models to project growth, adoption, and capacity needs across iCloud services. Mine structured and unstructured data to identify new opportunities and questions worth pursuing. Present findings and recommendations to audiences ranging from engineers to executives, influencing roadmap decisions. Collaborate cross-functionally with engineering, design, and business partners throughout the product development lifecycle.