CLM Analyst — Apple Retail Online

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.

The CLM Analyst supports Customer Insights and Lifecycle Marketing (CLM) analysis for the marketing organization, helping translate customer journey and campaign performance data into insights that inform CLM strategy. This role partners closely with Marketing, Decision Automation, and Database Marketing teams to build AI-assisted tools and rigorous test designs that improve targeting, creative, and timing decisions across the customer lifecycle.

The Retail Online Analytics team is responsible for providing insights, analytical solutions, and intelligent systems to Commercial Management, Commercial Marketing, Digital Merchandising, Online Product Management, Retail Contact Center, as well as Finance and other partner teams.

We are looking for a motivated, detail-oriented analyst to support Customer Insights and CLM Analysis across the marketing organization. This person will work at the intersection of customer journey analytics, lifecycle marketing performance, and applied AI — helping the team move from raw data to clear, actionable recommendations.

The CLM team relies on triangulating signals from multiple data sources — campaign performance, customer behavior, and experimentation results — to understand what’s driving (or holding back) customer engagement and lifetime value. This role will help build that end-to-end view, from data pull through to insight, and will increasingly take ownership of specific CLM analyses and reporting as they ramp up.

A meaningful part of this role involves developing lightweight applications and AI-assisted workflows (e.g., LLM-powered summarization, automated reporting, anomaly detection) that make CLM insights faster to produce and easier for stakeholders to consume. The analyst will also support test design and measurement for A/B tests spanning audience segmentation, creative variants, and send/display timing — helping the team validate what actually moves performance rather than relying on intuition.

Minimum Qualifications

Years of Experience — 2-4 years in marketing analytics, customer insights, CLM, or a related data/analytics role, with demonstrated exposure to campaign or lifecycle marketing data.
SQL & Python Proficiency — Working proficiency in SQL and Python for querying, cleaning, and analyzing large datasets, with the ability to translate business questions into repeatable analytical workflows.
Proficiency in applying ML techniques to marketing and customer datasets to derive deeper insights around customer segmentation, churn and retention prediction
Data Visualization & Tooling — Practical experience building dashboards and reports in Tableau (or similar BI tools), and familiarity with cloud data warehouse environments such as Snowflake.
Experimentation Fundamentals — Foundational understanding of A/B testing and statistical concepts (sample size, significance, variance), with hands-on experience supporting or analyzing test results.
Analytical Problem-Solving — Ability to synthesize data from multiple sources to identify patterns, evaluate marketing performance, and surface actionable recommendations.
Communication Skills — Strong written and verbal communication skills, with the ability to translate technical findings into clear, business-relevant insights for cross-functional partners.
Collaborative Mindset — Comfort working cross-functionally with Marketing, Analytics, and Engineering teams in a fast-paced, evolving environment, with curiosity toward AI-assisted analytics tools and methods.

Preferred Qualifications

Snowflake & Tableau Experience — Hands-on exposure to Snowflake for querying and organizing large marketing/customer datasets, and to Tableau for building dashboards that make CLM performance trends easy to interpret.
AI/LLM-Assisted Analytics Exposure — Familiarity with using AI or LLM-based tools to accelerate query writing, data exploration, or reporting workflows, with an interest in expanding this into more advanced tool-building.
Marketing or Customer Lifecycle Knowledge — Prior experience related to customer lifecycle marketing, customer segmentation techniques and journey analysis, providing helpful context for CLM-specific analysis.
A/B Testing for Marketing Applications — Exposure to designing or analyzing experiments specifically around marketing levers such as audience targeting, creative variation, or send timing, beyond general experimentation fundamentals.
Quantitative Academic Background — A degree or substantial coursework in a quantitative field such as Statistics, Economics, Data Science, or a related discipline, with demonstrated application to real-world analysis.
Cross-Functional Collaboration Experience — Prior experience working with or presenting to non-technical stakeholders, translating data findings into clear, actionable recommendations.