US Wearables Analytics & Individual AI Lead

Apple•Cupertino, CA

22h

About The Position

As the US wearables market intelligence analyst and tooling expert on Apple’s US Business Planning team, this role drives the weekly market intelligence cadence for Apple’s wearables portfolio across US Consumer Retail and Carrier routes-to-market. The position monitors competitive launches, pricing shifts, promotional activity, and campaign performance, translating complex market dynamics into actionable recommendations for sales leadership. The role also builds scalable infrastructure for market intelligence by turning recurring manual analysis into repeatable, self-serve reporting and integrating AI capabilities. It leads the Individual AI charter through custom AI briefing agents, prompt-engineering frameworks, and automated presentation workflows. The work combines econometric modeling, including hedonic price regression, with emerging AI capabilities to create predictive, decision-ready intelligence. The role partners with Business Planning, Decision Intelligence, DataOps, and BizOps teams to identify valuable analytics use cases and scale automated solutions.

Requirements

At least 5 years of hands-on analytical experience in market intelligence, business planning, sales operations, data analytics, or category management within consumer electronics, telecommunications, or retail.
Demonstrated success in consumer or business intelligence, product marketing, product management, commercial management, market research, finance, or strategy planning.
Strong interest in and familiarity with the wearables ecosystem, including smartwatches, health and fitness trackers, emerging form factors, true wireless audio, and core accessories.
Ability to connect market share movements, inventory trends, and competitor promotional activity to internal run-rates and current-quarter sales pacing.
Track record of building automated dashboards and self-serve reporting using Tableau, Power BI, or similar modern BI tools.
Experience with Python or R for data wrangling, automation, and data pipeline scripting.
Ability to operate in a fast-moving, high-visibility environment while supporting multiple senior cross-functional stakeholders.
Bachelor’s degree or equivalent experience required.

Nice To Haves

Familiarity with or strong curiosity about applying modern AI/LLM tools to streamline research synthesis and reporting workflows.
Experience building custom LLM agents, prompt-engineering pipelines, or automated briefing tools such as RAG or agent workflows.
Self-starter who thrives in a fast-paced environment and can balance weekly forecasting deadlines with longer-term tooling projects.
Expert proficiency in Keynote and Excel, with an eye for clean, minimalist visual design and the ability to translate complex data into concise slides.
MBA preferred.

Responsibilities

Own weekly aggregation and analysis of market share, syndicated data, channel sell-through, and promotional intelligence across smartwatches, adjacent wearable form factors, personal audio, and accessories.
Partner with sales planning, commercial, and demand forecasting teams across Consumer and Carrier channels to assess current-quarter trajectory against external market dynamics and identify run-rate risks, pacing anomalies, and forecast vulnerabilities.
Track competitor launch cadences, promotional changes, and category average selling price shifts, and summarize their implications for leadership each week.
Design, develop, and maintain automated tools, dashboards, and data models that scale market intelligence across US sales channels.
Build automated code and self-serve reports to eliminate recurring manual data pulls, and implement modern AI/LLM tools to accelerate synthesis of market reads and research reports.
Design, build, and deploy custom AI briefing agents to automate data retrieval, summarize market signals from multiple sources, and assist with executive slide generation.
Work with third-party data providers to validate data health, flag anomalies, manage recurring delivery cadences, and maximize the value of research investments.
Partner with Decision Intelligence, DataOps, and BizOps teams to test, shape, and advance experimental AI models toward production and implementation.
Develop and lead pricing and benchmarking frameworks, including spec-adjusted hedonic regression, using internal data and syndicated market sources.
Synthesize complex datasets into concise Keynote presentations and executive-ready summaries for sales leaders.