This role turns sponsorship data into clear, client-ready insight for some of the biggest brands in sports. The candidate will help build and maintain a proprietary, multi-brand sponsorship valuation model — working across Tableau Prep, Excel, and client decks — with guidance from senior team members. The ideal candidate is comfortable in the data (cleaning, joining, and QA-ing reporting pipelines) and is building toward owning larger workstreams and client relationships independently. A modern, efficient operator who uses AI tools to work faster and smarter is a strong fit.
• Support and help maintain Tableau Prep flows and the underlying data pipeline that feeds the sponsorship valuation model, under guidance from senior analysts.
• Mine, clean, and analyze data from brand, league, team, and third-party sources to evaluate sponsorship effectiveness and fan engagement.
• Own select recurring reports end to end (e.g., seasonal recaps, dashboards) with increasing independence over time.
• Maintain Python-based data integrations and Excel models; flag data gaps or breaks and help troubleshoot them.
• Translate data findings into clear, client-ready insights and recommendations, with senior review before final delivery.
• Contribute to client-facing decks — property evaluations, renewal recommendations, RFP support — and take on more of the narrative and strategic framing as skills develop.
• Participate in client meetings and status updates; take on direct client contact as trust and reps build.
• Use AI tools (e.g., Claude) to accelerate analysis, speed up reporting, and reduce manual, repetitive work.
• Partner with account teams and client stakeholders to understand business questions and define analytical approaches.
• Liaise with data vendors and league/team data teams to gather data and validate sources.
• Contribute to documentation of processes and tools that improve data accuracy and reporting consistency.
• Bachelor’s degree in Statistics, Data Science, Business Analytics, Economics, Marketing, or a related field.
• 2–4 years of experience in sports, media, or marketing analytics, research, or insights.
• Hands-on experience building dashboards and reports in Tableau Desktop.
• Strong Excel skills (formulas, pivot tables, data manipulation); solid PowerPoint.
• Strong analytical, quantitative, and problem-solving skills, with high attention to detail.
• Ability to communicate complex analyses in a clear, organized manner.
• Comfort using AI tools (e.g., Claude, ChatGPT) as part of day-to-day analytical work.
• Exposure to Tableau Prep or other data-pipeline / ETL tools.
• Working knowledge of Python or SQL.
• Familiarity with sponsorship measurement sources and vendors (e.g., Relo Metrics, Nielsen, fan/consumer survey platforms).
• Experience presenting analysis directly to clients or senior stakeholders.
