Data Scientist, Business Ventures at U.S. Soccer Federation
Job Description
U.S. Soccer Overview
The U.S. Soccer Federation exists in service to soccer. Our aim is to ignite a national passion for the game. Because we believe that soccer is more than a sport; it is a force for good.
We understand the importance and the power of teamwork, on and off the pitch. That is why we work closely with our Federation partners and members, to inspire, support and guide every level of the game: from the grassroots to the National Teams. We want to bring soccer into every home and every community, right across America. Because we believe that soccer can transform lives like no other sport. Soccer can represent the best of U.S.
U.S. Soccer is in a period of significant growth, with ambitious plans for U.S. Soccer in the near and far future. We are, therefore, looking for dynamic servant leaders to join us on this journey: in service to soccer. Applicants must be able to demonstrate visionary leadership, analytical decision-making, professional flexibility, and an empathic management style that builds bold teams and delivers globally significant results.
Position Description
U.S. Soccer is seeking a Data Scientist to help transform data into actionable insights, intelligent products, and measurable business outcomes. The Data Scientist will join the Business Ventures team, advancing data-driven decision-making across the Federation, working with stakeholders throughout Commercial, Marketing, Ticketing, Membership, E-commerce, Advancement, Product, and Technology to identify where analytics, machine learning, experimentation, and artificial intelligence can improve performance and accelerate growth.
This is not a reporting role. The Data Scientist will take ownership of complex business problems, translate them into analytical frameworks, and work with partners to put those solutions into practice. Projects may include understanding what drives soccer fandom in the United States, forecasting demand for matches and products, predicting fan behavior, improving audience segmentation, measuring campaign effectiveness, developing customer intelligence, and building AI-powered tools that make data more accessible across the organization.
The ideal candidate combines strong technical capabilities with curiosity, business judgment, and communication skills. They should be comfortable working with large and sometimes imperfect datasets, able to explain complex findings to nontechnical audiences, and genuinely interested in what creates and sustains a soccer fan—why someone attends a match, tunes in, buys a jersey, or brings a child into the game.
Primary Responsibilities
Predictive Modeling and Machine Learning
- Develop, validate, and deploy predictive models supporting fan engagement, ticket sales, membership growth, retention, e-commerce, fundraising, and marketing—including propensity, classification, forecasting, segmentation, recommendation, and customer-value models.
- Develop a deep understanding of what drives soccer fandom in the United States: how fans discover the sport, what converts casual interest into attendance, viewership, and purchase, and how those drivers differ across markets, teams, and competitions.
- Forecast demand for matches, broadcasts, and products, and isolate the primary drivers behind changes in attendance, viewership, and revenue so stakeholders understand not just what is projected, but why.
- Select appropriate statistical and machine-learning methods based on the business problem, available data, and intended use of the results.
- Establish model evaluation, monitoring, documentation, and regression-testing processes so solutions remain reliable over time.
- Develop audience segments and analytical frameworks that improve personalization, targeting, acquisition, retention, and lifetime value, and evaluate customer journeys to deepen relationships with current supporters and reach new soccer audiences.
- Partner with Marketing, CRM, and other stakeholders to embed model outputs into campaigns, platforms, and lifecycle strategies.
- Identify opportunities to responsibly apply generative AI, natural-language interfaces, and intelligent automation, and contribute to AI-powered tools that help employees answer their own questions.
Communication and Cross-Functional Partnership
- Work directly with stakeholders to translate broad or ambiguous business questions into clearly defined analytical problems.
- Present findings and recommendations clearly and compellingly to both technical and nontechnical audiences, and create visualizations and decision-support materials that make complex analysis actionable.
- Build strong relationships across departments and serve as a trusted analytical partner.
- Balance multiple projects and priorities while maintaining high standards for accuracy, transparency, and execution.
Requirements
Minimum Qualifications
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