EXL Analytics is seeking a Data Scientist (Econometrics) to support the Local Business Optimization (LBO) initiative, aiming to help sports clubs unlock new revenue opportunities and optimize local business strategies through data-driven insights.
Requirements
- Proficiency in Python, R, SQL.
- Experience with A/B testing, clustering algorithms, predictive modeling.
- Skills in statistical analysis, predictive modeling, clustering, and feature engineering. Proficient with Python, R, and SQL; experienced in working with varied data sources and ETL.
- Knowledge of model validation methods such as cross-validation and ROC/AUC.
- Familiar with modern machine learning libraries like scikit-learn, TensorFlow, and PyTorch, adhering to current best practices.
- Proficiency in using AWS CodeCommit for version control and collaborative code management within cloud-based development environments.
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.
Other
- 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.
- 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.
