Data Scientist in Digital Transformation team at Lavazza implementing machine learning models and managing model lifecycle within Agile squads. Focusing on solving real business problems.
About the role
- 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.
Benefits
- Health insurance
- Flexible working arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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