Responsibilities

• Multi-Source Analysis & Insights
• - Audience Segmentation & Behavior Analysis: Analyze attendee demographics, behaviors, and content consumption patterns within an experience to identify what resonated most with specific audience cohorts.
• - Brand Health & Sentiment Analysis: Synthesize qualitative data from post-event surveys, focus groups, and social listening to measure shifts in brand affinity, Net Promoter Score (NPS), and message retention.
• - Business Impact Modeling: Tie experience engagement data back to client business outcomes. This includes analyzing CRM data to track post-experience sales velocity, pipeline acceleration, or customer retention.
• Data Operations, Optimization & Infrastructure
• - Data Centralization Projects: Support the centralization of agency data by configuring systems (like Airtable) to act as core repositories, eventually feeding into our purpose built and proprietary platform.
• - Big Data Analytics Infrastructure: Work with tools like BigQuery to store, clean, and analyze massive datasets (such as beacon data and spatial metrics).
• - Process Automation: Help automate routine data collection workflows, specifically supporting our growing workbench of strategist-facing tools.
• - Data Cleaning & Consolidation: Merge disparate data streams—like registration lists, on-site engagement logs, and third-party research—into unified datasets for analysis.

Requirements

• Experience: 3–5 years of experience in marketing analytics, data strategy, or decision science—ideally within an agency, consulting, or brand-side marketing environment.
• Education: Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Data Science, Economics, Business Analytics, Psychology, or a related discipline.
• A versatile mindset that balances analytical rigor with inspired creativity, with the ability to distill complex data sets into compelling narratives.
• A working knowledge of AI and agents, with a proactive approach to leveraging these technologies to enhance our workflows, processes, and overall capabilities.

Preferred

• Data Analysis & Scripting: Strong knowledge of Python or R for statistical analysis.
• Databases & Data Ops: Experience with BigQuery (or similar cloud warehouses) and Airtable for data management and centralization.
• BI & Visualization: Hands-on experience building clear, intuitive dashboards in Looker Studio , Tableau , or Power BI .

Benefits

• We’re Employee-Owned: Every GPJer shares in our success. We offer an Employee Stock Ownership Plan (ESOP) providing employees with an ownership interest, alongside an employer-matching 401(k) plan (no vesting period) and excellent low-cost healthcare options.