WW RCC Data Scientist
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About the role
In this role, you will define how we measure the performance of automated customer interaction systems, build analytical frameworks to compare outcomes across interaction models, and deliver insights that determine where automation creates value and where human expertise remains essential. You will work with structured operational data and unstructured conversation data at scale, applying NLP, experimentation, and statistical modeling to drive decisions that directly impact revenue, cost, and customer experience.You will be a part of the World Wide Analytics team within Retail Contact Center, partnering closely with engineering, operations, and product teams to measure and optimize performance across our global contact center operations.
Responsibilities
- Build analytical frameworks that enable rigorous comparison of customer outcomes, cost efficiency, and experience quality across different service delivery models - informing strategic decisions on where automation adds value and where human expertise is essential.
- Apply statistical and ML techniques to understand customer interaction patterns - including contact drivers, resolution effectiveness, repeat contact behavior, and the comparative economics of different service channels.
- Build and maintain scalable analytical pipelines, models, and tooling that enable ongoing measurement and monitoring - moving beyond one-off analysis to production-grade analytical solutions.
- Develop self-service analytical tools-including automated reporting, interactive dashboards, and curated datasets-that empower business stakeholders to access routine performance insights independently.
Requirements
- Familiarity with cloud data platforms, particularly Snowflake and AWS.
- Master's degree in a quantitative field.
- Previous experience measuring the performance of automated customer interaction systems (e.g., IVR, virtual assistants, self-service channels).
- Experience in customer experience analytics, contact center operations, or customer interaction measurement.
- Hands-on experience leveraging LLMs/Generative AI to improve productivity and generate new insights.
- Previous experience in stakeholder management and large-scale cross-functional project work.
- Masters Degree preferred
- Contributes to an inclusive environment through respecting each other's differences and having curiosity to learn.
- Demonstrates Apple's values
- 8+ years experience working within business analytics, we
Additional Information
Imagine what you could do here! The people here at Apple don't just create products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work. Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things. We are seeking a highly motivated Senior Data Scientist to help inform innovation strategy by leading analysis into behavioral segmentation, pilot measurement, text analytics and AI tools integration. In this role, you will be part of Apple Store Online, with a particular focus on Retail Customer Care (RCC) performance and decision support. Using data and quantitative techniques, the decision support team acts as a consultant, providing insights and recommendations to inform the org's innovation strategy and to drive operational performance improvements at vendor and Apple contact center sites.
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