This role turns sponsorship data into clear, defensible recommendations for some of the biggest brands in sports. The candidate will own a proprietary, multi-brand sponsorship valuation model end to end — from the underlying data pipeline through the final client-facing slide — and must be as comfortable building and troubleshooting a Tableau Prep flow as presenting the strategic story it tells to senior client stakeholders. This is a hands-on technical and strategic role: the candidate builds the pipeline, owns the model, and leads the room. The ideal candidate is also a modern, efficient operator — someone who uses AI tools to work faster and smarter, not just someone who can run a dashboard. This role also manages and mentors junior analysts.
• Own and maintain a proprietary, multi-brand sponsorship valuation model end to end — architecture, custom weighting, benchmarking, and cost-efficiency inputs.
• Build, document, and troubleshoot Tableau Prep flows that blend disparate data sources (media exposure, survey, market share, social, broadcast, ticketing data) into clean, analysis-ready outputs.
• Develop and maintain Python-based data integrations (API connectors, automated data pulls) and advanced Excel models, including ROI and incremental sales analyses.
• Build documentation and repeatable processes so the model’s logic, data lineage, and refresh cadence don’t live in one person’s head — a standing priority for this role.
• Translate complex data into client-ready presentations and defensible strategic recommendations — property evaluations, renewal recommendations, RFP support — from single-team deep dives to league-wide landscapes.
• Lead recurring reporting across multiple accounts (seasonal recaps, quarterly dashboards, scorecards) and independently manage senior client stakeholder relationships with little day-to-day oversight.
• Identify the audience and the “so what” for every deliverable before building it — this role is expected to operate at a strategic level, not just produce data.
• Use AI tools (e.g., Claude) to accelerate analysis, prototype models, and automate reporting workflows.
• Proactively identify where AI and automation can replace manual, repetitive work across the team’s reporting.
• Mentor and review the work of junior analysts; develop their technical and strategic skills.
• Manage a pipeline of evaluation requests, model fixes, and data gaps; set priorities with account leads.
• Partner with data vendors and research providers on data quality, dashboards, and new sources.
• Bachelor’s degree in Statistics, Data Science, Business Analytics, Economics, Marketing, or a related field.
• 5+ years of experience in sports, media, or marketing analytics, research, or insights, including direct ownership of a complex data model or reporting pipeline.
• Hands-on, advanced experience with Tableau Desktop and Tableau Prep — able to build and debug pipelines independently, not just consume dashboards.
• Advanced Excel (complex formulas, model-building); strong PowerPoint.
• Working knowledge of Python and/or SQL for data integration and automation.
• Practical, hands-on experience using AI tools (e.g., Claude, ChatGPT) in day-to-day analytical work.
• Strong strategic and narrative skills — demonstrated ability to turn data into a clear, client-ready story and defend it to senior stakeholders.
• Prior experience managing or mentoring junior team members.
• Familiarity with sponsorship measurement sources and vendors (e.g., Relo Metrics, Nielsen, fan/consumer survey platforms).
• Experience owning a client-facing analytics practice with minimal senior oversight.
