Data Scientist - Football Operations & Media

This role sits at the intersection of football strategy and media analytics, leveraging data science to enhance both the on-field game and the off-field fan experience. You will build predictive models and decision tools that optimize game scheduling, evaluate rule changes, and forecast viewership—driving innovation across Football Operations, Broadcasting, and NFL Media.

• Develop predictive models for game-by-game viewership and integrate them into scheduling workflows
• Simulate trade-offs (e.g., competitive balance, travel, bye weeks) to support flex scheduling decisions
• Create weekly dashboards and scenario analyses for tentpole events and regular-season slates
• Quantify impacts of rule changes (e.g., kickoff format) on gameplay, safety, and scoring
• Evaluate officiating technologies using tracking and vision data; define KPIs for adoption
• Analyze player/ball tracking data to assess game quality, parity, and fan engagement
• Collaborate with the Big Data Bowl community to source and test innovative analytics methods
• 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 (Gurobi/OR-Tools)
• Experience turning probabilistic forecasts into decision tools (e.g., simulations, scenario analysis)
• Familiarity with audience/ratings data (e.g., Nielsen), time series forecasting, and causal analysis
• Strong communication skills to translate complex models 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 (e.g., synthetic control, DiD, double ML)
• MLOps experience (e.g., Airflow, feature stores, model monitoring)
• Dashboarding skills (e.g., Tableau, Power BI, Mode)
• Understanding of media ecosystem constraints (e.g., network contracts, tentpole scheduling)