Data Scientist (Econometrics) supporting LBO initiative for sports clubs with data-driven insights. Focus on revenue optimization through actionable analytics and advanced modeling techniques.
Responsibilities
Collect, clean, and analyze large, complex datasets from diverse sources; streamline and integrate data collection processes and optimize query performance
Design, develop, and implement advanced data science econometrics models and conduct exploration analyses to uncover trends in local market performance, fan engagement, sponsorship, ticketing, and other revenue streams.
Refine and enhance existing opportunity models using test-and-learn approach, including A/B testing and clustering algorithms.
Develop and deploy predictive models to forecast key economic and sports business metrics (e.g., incremental revenue, sponsorship ROI, fan engagement growth).
Monitor developed AI/ML models for performance drift and be able to re-train degraded models when applicable.
Support Club Business Development and Clubs by translating complex models into actionable analytical insights to help clubs efficiently reach their revenue opportunity.
Define and track KPIs and success metrics, partnering with Club Business Development to measure program impact.
Work closely with Data Engineering team for data integration and model production deployment.
Present findings and recommendations in a compelling and visually engaging manner.
Stay current with industry trends in sports analytics, econometrics and data science.
Requirements
Bachelor’s or Master’s degree in Econometrics Data Science, Statistics, Computer Science, or a related field.
3+ years of experience in data science, analytics, or business intelligence, preferably in sports.
Proficiency in Python, R, SQL.
Experience with A/B testing, clustering algorithms, predictive modeling.
Strong attention to detail with a focus on maintaining rigor across data analysis, modeling, and reporting.
Strong communication and storytelling skills with the ability to influence stakeholders.
Passion for sports and a deep understanding of sports leagues’ business model.
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