Data Scientist

Data Scientist - Sports Media Valuation & Insights

• 3-Month Contract
• Remote (US Based but preference for New York based)
• Rate DOE Per Hour

This is a unique opportunity to play a critical role in the valuation of global sports media and sponsorship assets. Working on a high-profile freelance assignment, you will help validate and strengthen predictive models that will directly inform commercial decisions across multiple major sports leagues.

The Company

They are a specialist organisation operating at the intersection of sports, media, sponsorship, and advertising technology. Their work focuses on helping rights holders and commercial partners better understand and monetise media and sponsorship inventory across global sporting audiences. With active projects supporting major sports leagues, they are looking for an experienced contractor who can deliver immediate impact.

The Role and Deliverables

• Review, audit, and reverse engineer existing Excel-based predictive valuation models.
• Validate assumptions, methodologies, and calculations across sponsorship, media rights, virtual advertising, and LED inventory valuations.
• Sense check models built using multiple commercial and audience-related variables to ensure they are robust and commercially credible.
• Translate audience, viewership, CPM, and distribution data into clear valuation insights and commercial recommendations.
• Produce board-level insights and support strategic decision-making for sports media and sponsorship programmes.
• Communicate complex modelling logic and assumptions clearly to both technical and non-technical stakeholders.

Your Skills & Experience

• Strong experience within sports media, sponsorship valuation, broadcast economics, or a closely related commercial media environment.
• Deep understanding of media inventory, CPM-based valuation frameworks, audience measurement, media rights, and advertising ecosystems.
• Working knowledge of virtual advertising and LED sponsorship inventory within sports broadcasting environments.
• Advanced Excel modelling capability, including scenario modelling, sensitivity analysis, and financial valuation frameworks.
• Experience reviewing, auditing, and improving complex predictive models.
• Ability to create commercially meaningful insights from large datasets and modelling outputs.
• Strong stakeholder communication skills, with the ability to explain modelling assumptions and recommendations to executive audiences.
• Comfortable working independently in a fast-paced project environment with immediate deliverables.