The NFL is looking to leverage data science and analytics to better understand and predict football game viewership by analyzing game competitiveness, equity, leverage, and excitement.
Requirements
- Advanced knowledge of R
- Basic knowledge of python
- Experience with the tidymodels package in R
- Experience building Shiny apps
- Experience building R packages
- Advanced knowledge of Python
- Familiarity with SQL
Responsibilities
- Build, validate, and automate statistical/machine learning models for Football Operations/Media related data, including game competitiveness, equity, leverage, and excitement, and leverage those factors and others to predict NFL game viewership
- Curate and enhance the NFL’s Football Operations data analytics projects, including data cleansing, analysis, and reporting
- Work within the central data and analytics team to develop new and relevant metrics for cross-sectional usage across the league
- Collaborate with the Football Operations group on data and analytics events, including the Big Data Bowl
- Perform ad-hoc analysis and reporting on request
- Collaborate with Media Reporting and Broadcast departments regarding metrics for game viewership and projected viewership
Other
- 7+ years of experience of building statistical models in sports
- Strong written and verbal communication skills in English
- Ability to analyze highly sensitive and confidential data
- Strong knowledge of the National Football League and its teams
- Attend in-person meetings at various points in the NFL calendar
