Data Scientist
Harnham · New York, NY · 1 mo ago
AnalystFull-time
The Role
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.
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.
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.