Associate Director, Digital Insights & Analytics

Responsibilities

• Build end-to-end measurement frameworks for digital journeys and behavior across channels, defining stage KPIs, event instrumentation, and north-star metrics to pinpoint friction and drive conversion.
• Aggregate and share cross-brand digital learnings via standardized playbooks, taxonomies, and reporting cadences; align stakeholders on common KPIs and data quality for scalable, data-driven decisions.
• Deliver marketing mix modeling and attribution within a disciplined framework—set inputs and governance, validate incrementality, and integrate outputs into planning to optimize budgets and channel performance.
• Drive the integration, operationalization, and scaling of AI platforms and capabilities across the market & business analytics stack—including adoption of machine learning and generative AI for digital consumer segmentation, experimentation, and insight automation to accelerate decision-making and business impact.
• Support measurement and optimization of A/B and multivariate tests to improve website and mobile experiences, increase conversion rates, and reduce drop-off across key funnel stages
• Lead predictive analytics initiatives and build advanced audience strategies (e.g., lookalikes, churn risk segments, product affinities, propensity) to power targeted media, onsite personalization, and lifecycle communications.
• Create executive-caliber visual storytelling artifacts—decks, dashboards, and one-page syntheses—that crystallize digital insights, quantify impact, and escalate actions to drive cross-functional accountability.
• Analyze performance against north-star KPIs aligned to broader business goals (conversion, retention, LTV, CAC:LTV), providing actionable insights and variance explanations.
• Manage external analytics partners and tools, ensuring deliverables align to business priorities and performance targets; assess competitive landscape and data/analytics advancements to inform best practices and innovation opportunities.
• Partner with technology teams to improve instrumentation, data quality, and integration of tools, methods, and processes that support scalable, reproducible analytics.

Requirements

• 8+ years of experience with relevant web/mobile analytics reporting and analysis. 8+ years of experience as a Marketing Data Analyst or similar role, with a focus on ecommerce and digital marketing analytics.
• Bachelor’s degree (or MBA) in Business Analytics, Data Analytics, Marketing, Mathematics, Statistics, or related quantitative field
• Outstanding analytical, critical thinking, and organizational skills with high attention to detail. Ability to focus on both strategy and execution.
• Deep understanding of marketing metrics, attribution models, and campaign performance measurement, with the ability to provide strategic recommendations.
• Experience in developing/maintaining analytics dashboards and developing/maintaining reporting tools for self-serve reporting.
• Passionate about customer-centricity and data-driven strategy, with the ability to effectively communicate and influence key stakeholders.
• Exceptional at finding trends in the data, articulating the “so what,” and translating insights into strategic, actionable recommendations.
• Excellent written and verbal communication and data story-telling skills, including the ability to clearly present findings and recommendations to diverse stakeholders.
• Experience in defining metrics and KPIs, visualizing and presenting results, and tying insights back into business strategies and goals.
• Advanced SQL experience
• Expertise with web analytics tools, including Google Analytics (GA4 a plus), ContentSquare, Dynamic Yield, Similarweb, Semrush etc.
• Experience with CRM management tools, customer data platforms (Hightouch, etc.)
• Experience with data visualization tools (Tableau, Power BI, etc.)
• Proficient in MS Office core suite (Excel, PowerPoint, Word, Outlook)
• Curious, inquisitive, proactive, and interested in digging for insights in data, as well as learning new tools and techniques.
• A team player attitude and thrive in ambiguity, proactively identifying opportunities for impact.
• Ability to work effectively in a fast-paced, team environment.
• Proficiency with more advanced statistical modeling techniques is a bonus (e.g. clustering, classification, segmentation, multiple regression, etc.).