Data Scientist Football Media & Operations

@ EXL

Overview

The Data Scientist Football Media & Operations role at EXL sits at the intersection of football strategy and media analytics. You will leverage data science to enhance on-field performance and off-field fan experience by building predictive models and decision tools that optimize game scheduling, evaluate rule changes, and forecast viewership.

Responsibilities

• Develop predictive models for game viewership integrated into scheduling workflows
• Simulate trade-offs for flex scheduling and competitive balance
• Create weekly dashboards and scenario analyses for key events
• Quantify impacts of rule changes on gameplay, safety, and scoring
• Evaluate officiating technologies using tracking and vision data
• Analyze player/ball tracking data to assess game quality and fan engagement
• Collaborate with the Big Data Bowl community for innovative analytics
• Productionize pipelines for ratings-aware scheduling and scenario refreshes
• Ensure reproducibility, versioning, and auditability of models and workflows

Required Qualifications

• 3–6+ years in data science, operations research, or quantitative analytics
• Proficiency in Python (pandas, scikit-learn, statsmodels, PyMC), SQL, and optimization tools
• Experience turning probabilistic forecasts into decision tools
• Familiarity with audience/ratings data, time series forecasting, and causal analysis
• Strong communication skills for non-technical stakeholders

Preferred Qualifications

• Experience with player/ball tracking datasets and spatial modeling
• Exposure to football strategy metrics and expected points modeling
• Knowledge of causal inference techniques and MLOps experience
• Dashboarding skills with tools like Tableau, Power BI, or Mode
• Understanding of media ecosystem constraints and scheduling

Key skills/competency

Data Science, Python, SQL, Predictive Modeling, Analytics, Optimization, Football Analytics, Dashboarding, Causal Analysis, MLOps