Director, Analytics

XFL Properties LLC DBA United Football League• US,

14h•$115,000 - $135,000•Remote

About The Position

The Director of Analytics is a key leadership role responsible for transforming the UFL's data into actionable business decisions. This individual will lead the development of pricing and yield models, customer segmentation, and revenue forecasts. The role requires a hands-on approach, including writing SQL, building models, and designing dashboards, while also establishing data standards and communicating insights to non-technical stakeholders. A primary near-term goal is to modernize reporting by transitioning from static, manual reports to self-serve tools, enabling stakeholders to explore business performance independently. This position is part of a growing Data & Business Intelligence function, working alongside a Data Engineer and CRM Manager, and will have significant influence on the UFL's data strategy. The ideal candidate is comfortable in an early-stage environment, prioritizes data quality, and focuses on building sustainable solutions. The role is remote with occasional travel.

Requirements

Bachelor's degree in a quantitative or business field (Mathematics, Statistics, Economics, Computer Science, or similar). An equivalent combination of education and hands-on experience may be considered
5-7 years of professional experience in analytics, including hands-on ownership of business-facing models: pricing, demand forecasting, customer lifetime value, segmentation, or campaign response. A track record of work that changed a business decision, not just answered a question
Analytics experience within sports, entertainment, or live events, including hands-on work with ticketing and revenue data (Ticketmaster/Archtics or similar systems)
Experience leading a migration from manual, static reporting to a self-serve analytics environment
Advanced SQL, including the ability to write and optimize complex queries against a modern cloud warehouse without help from an engineer, plus enough familiarity with data modeling and modern stacks (dbt, BigQuery, ETL/ELT concepts) to be a demanding, informed customer of the pipelines you depend on
Working proficiency in Python or R for analysis and modeling. Enough to build a forecast, run a statistical test, and validate your own work
Advanced skill with a modern BI platform (Looker, Tableau, Power BI, or similar), including designing self-serve, interactive dashboards
Proven ability to translate analysis for non-technical audiences and present recommendations directly to senior leadership
Comfort with ambiguity and a willingness to stay hands-on. Moving goalposts, incomplete data, problems that arrive as a vague question rather than a defined spec, and a role that owns day-to-day analysis alongside roadmap planning

Nice To Haves

Advanced degree in a quantitative field
Experience with CRM and marketing automation data (HubSpot, Salesforce) in an analytical capacity
Experience mentoring or directing junior analysts, interns, or fellows, and the appetite to build a team as the function expands over the next several seasons

Responsibilities

Serve as the analytics partner to Sales, Marketing, Partnerships, Finance, and Football Operations, embedded closely enough with each group that their leaders bring you problems early, not just requests late
Run the intake and prioritization of analytics work across the organization. Triage incoming requests into a visible backlog, sequence them against roadmap commitments, and make the call on what gets built, what gets a same-day answer, and what waits
Build and maintain the models that drive revenue: ticket pricing and yield management, demand and revenue forecasting, and customer lifetime value, applying predictive and statistical techniques where they earn their keep
Define who our fans are, what they're worth, and which groups to target for retention and acquisition, then hand those segment definitions to Sales and Marketing to execute against
Measure what worked. Evaluate the performance and ROI of marketing campaigns, sales efforts, partnership activations, and pricing decisions, and feed those findings into the next cycle
Lead the transition to interactive tools stakeholders can explore on their own, reducing the volume of one-off requests over time
Maintain the enterprise dashboards that track organizational KPIs, and make sure the people using them understand what they're looking at
Own the definitions layer: what each metric means, how it's calculated, where it comes from, and how consistently it shows up across everything the team produces
Own the accuracy and integrity of analytical output. Partner with the Data Engineer on the pipelines underneath it, and escalate data-quality issues at the source rather than working around them
Direct and mentor early-career analytics talent (interns, fellows, and analysts), scoping their work thoughtfully and including them in real projects rather than leftovers
Build data fluency across the organization, so stakeholders get better at asking questions and interpreting answers
Work within the team's development practices (standups, backlog grooming, sprint planning, and retrospectives). Take responsibility for how analytics work shows up in them, keeping it visible, scoped, and prioritized alongside engineering and CRM