Conversion Optimization Manager - Apple Retail Online

This role leads a team of analysts responsible for understanding and improving how customers engage with Apple's e-commerce site — from first click to completed purchase. You will oversee two core functions: conversion and site engagement analytics, and a dedicated A/B testing practice that enables data-driven decision-making across the online retail business. This is a highly collaborative role, partnering closely with merchandising, product, and marketing teams to surface insights that directly influence the online shopping experience. - Lead site engagement and conversion analytics — Own the team's analysis of customer behavior across the online shopping journey, including on-site merchandising performance, buy flow efficiency, and friction and fallout identification; translate findings into actionable recommendations for cross-functional partners. - Manage and grow the A/B testing function — Oversee the end-to-end experimentation practice, including test design, execution, statistical rigor, and results communication; establish standards and frameworks that scale the team's testing capability. - Deliver recurring and ad hoc reporting — Drive the development and maintenance of performance dashboards, journey analyses, and executive-ready reports that track conversion health and inform site optimization priorities. - Develop and mentor a high-performing analytics team — Provide strategic direction, coaching, and professional development for a team of data scientists and experimentation specialists, fostering a culture of curiosity, rigor, and impact. Analyze customer behavior across the full online shopping journey — including product discovery, page engagement, buy flow progression, and checkout fallout — to identify friction points and opportunities that improve conversion rates Evaluate on-site merchandising performance by measuring how customers interact with placements, modules, and promotional content, and connecting engagement signals to downstream purchase outcomes Lead the A/B testing practice from hypothesis through readout — partnering with product, merchandising, and marketing teams to design well-structured experiments, ensure statistical validity, and deliver clear, confident recommendations Define and maintain the team's core measurement frameworks, including conversion funnels, engagement metrics, and experimentation guardrails, ensuring consistency and reliability across all analyses Synthesize complex behavioral data into concise, executive-ready narratives that communicate the "so what" behind the numbers and drive prioritization decisions across the online retail organization Serve as the team's primary thought partner and escalation point — setting analytical standards, reviewing methodologies, and ensuring the quality and integrity of all work delivered to stakeholders 8+ years of experience in digital analytics, web analytics, or e-commerce analytics, with hands-on expertise in clickstream data analysis and customer behavior measurement across web and app platforms 2+ years of experience managing or leading a team of analysts or data scientists, including setting analytical direction, reviewing methodologies, and supporting team growth and development Highly proficient in SQL for large-scale extraction, transformation, and analysis of behavioral datasets, with demonstrated ability to work directly with raw clickstream data at scale Proficient in Python for data science workflows — including statistical analysis, behavioral segmentation, and process automation — with hands-on exposure to modeling or machine learning methodologies applied to real business problems Deep understanding of e-commerce fundamentals and the key drivers of traffic, engagement, conversion, and revenue — including funnel construction, fallout analysis, buy flow efficiency, and on-site merchandising performance measurement Proven experience leading an end-to-end A/B testing or experimentation practice — from hypothesis development and test design through sample size calculation, significance testing, and results communication — with strong fluency in statistical concepts including p-values, Type I/II error, confidence intervals, and sequential testing Hands-on experience with enterprise clickstream analytics platforms such as Adobe Analytics or Google Analytics, and data visualization tools such as Tableau or equivalent Experience applying advanced data science methodologies to customer behavior or conversion optimization problems — such as predictive modeling, propensity scoring, causal inference, or uplift modeling Familiarity with multivariate testing frameworks and experience scaling an experimentation program across a large digital commerce organization BA/BS in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field; advanced degree (MS or MBA) a plus Exceptional ability to translate complex analytical findings into executive-ready narratives and influence prioritization decisions with senior cross-functional stakeholders

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