[Hiring] Lead Web Analytics Analyst @Moburst

Role Description

We’re looking for a data-driven, proactive Lead Web Analytics Analyst for a part-time position to join our team. Someone who thrives on turning complex web and business data into actionable insights. This role is centered on advanced web analytics, tracking architecture, and data integration, using data as the foundation to drive performance across B2B digital initiatives.

• Lead the Web Analytics Data Architecture: Ensure high attention to detail in data collection, implementation, and reporting, including Server-to-Server (S2S) tracking/CAPI and integrating web analytics with advertising and CRM platforms.
• Generate Actionable Insights: Analyze company-wide data from multiple sources, providing actionable insights to improve traffic quality, attribution accuracy, performance, and ROI.
• Data Integrity & Auditing: Serve as the gatekeeper for data quality, continuously auditing tracking setups, identifying discrepancies, and ensuring accurate full-funnel measurement.
• Leverage AI for Efficiency: Use AI-driven analytics tools to automate reporting, detect anomalies, uncover trends, and enhance predictive insights.
• Collaborate and Communicate: Collaborate with cross-functional teams (Marketing, Product, Media, SEO) to drive data-informed decision-making. Present findings and tracking recommendations clearly to stakeholders, helping teams translate insights into action.

Qualifications

• 3+ years of experience in advanced web analytics and data analysis, preferably in a B2B environment.
• Deep Expertise in Google Analytics (GA4) including implementation, tracking configuration, and data modeling, encompassing the capability to implement GA4 and derive actionable insights (utilizing dashboards, reports, and our internal BI system).
• Advanced hands-on experience with Google Tag Manager (GTM), server-side tagging, and Consent Management Platform (CMP) systems.
• Expertise in Pixel/S2S integrations with advertising platforms (e.g., Facebook, LinkedIn, Google Ads).
• Familiarity with AI-driven analytics and data visualization tools - A must.
• Hands-on experience with alternative analytics platforms; Adobe Analytics experience is a plus.
• Strong ability to work with multiple datasets, identify patterns, map user journeys, and generate actionable technical recommendations.