Senior Analyst, Sephora Media Network

Develop and apply methodologies that measure incrementality, omnichannel impact, new-customer acquisition, audience performance, promotional effects, and media contribution. Apply foundational media mix modeling (MMM) concepts and retail media network (RMN) knowledge to support channel contribution analysis, budget-allocation insights, and cross-channel measurement recommendations. Use approved AI and machine-learning capabilities to accelerate data exploration, anomaly detection, insight synthesis, forecasting, documentation, and first-draft analytical storytelling. Develop reusable AI-assisted workflows, prompts, agents, or analytical tools that reduce manual effort while keeping human review and business judgment at the center. Own recurring onsite and offsite reporting, including ROAS, revenue and spend trends, new-to-brand performance, campaign hindsight, and executive business updates. Translate performance into clear, commercially relevant narratives and recommendations for Brand Marketing, Media, Finance, leadership, and brand partners. Build repeatable quality-assurance processes that reconcile platform, API, dashboard, finance, and source-of-truth data before insights are distributed. Serve as a key analytics partner to cross-functional teams, translating stakeholder priorities into clear business questions, analytical requirements, and actionable deliverables. Present findings and recommendations to business partners and leadership to inform campaign optimization, investment, and reporting decisions. Champion process improvements, documentation of shared ways of working, and self-service adoption of analytical best practices. 2-4 years of experience in marketing analytics, retail media, paid media measurement, business intelligence, data science, or a related field. Strong SQL skills and working knowledge of Python or R; experience with Databricks, Adobe Analytics, Google Analytics, or comparable analytics platforms. Experience building dashboards and data visualizations and translating complex findings into concise, decision-ready stories. Understanding of ROAS, attribution, incrementality, new-to-brand measurement, forecasting, campaign optimization, and foundational media mix modeling (MMM) concepts. Familiarity with retail media networks (RMNs), including onsite and offsite media ecosystems, common ad products, and measurement approaches. Hands-on fluency with enterprise-approved generative AI or machine-learning tools for analysis, automation, documentation, or insight generation. Ability to validate AI-generated outputs, identify errors or bias, protect confidential data, and apply responsible-AI and data-governance standards. Strong problem-solving, quality-assurance, communication, stakeholder-management, and project-management skills. #LI-AZ1