ESPN Analytics is a multidisciplinary group where all members have deep knowledge of sports, statistics, databases, coding across multiple languages, and storytelling. Combining best-in-the-industry data with advanced mathematics and statistical modeling skills, ESPN Analytics has created storytelling tools and metrics that have improved the evaluation of team and player performance, such as Total QBR and power ratings for football, basketball, and more. These products make fans better informed and help keep ESPN at the cutting edge of sports statistical analysis.
The Sports Data Engineer will serve as both a core developer and a modeling contributor within the team, setting forth a vision for the modernization of its tech stack, helping guide and mentor more junior members, and driving development across new and existing metrics. This includes gathering, wrangling, and verifying data, writing production-quality code to implement and automate those metrics at scale, and contributing to the statistical and predictive models that power them, including leveraging AI and ML tooling where appropriate. Candidates need to have a strong command of internal analytics metrics and be comfortable owning work from raw data through model output to published product. The Data Engineer will help the team tell stories in the most engaging and accurate way, matching the storytelling to the medium. Translating the complex into understandable language is a key requirement of the job.
The Sports Data Engineer will work collaboratively with other members of the Analytics team as well as engage consistently with outside partners, both inside and outside of Disney, in order to advance the team's goals. This will include exploring technical solutions with partners to better disseminate, organize, and display the team's data and metrics and helping develop new products to serve this purpose.
Responsibilities:
- Write optimized, production-quality code to transform data into automated metrics across ESPN platforms and internal research tools, leveraging AI tools to enhance development speed and output quality
- Develop data requirements for new metrics and help establish a technical methodology for production execution, including feature engineering and model architecture decisions
- Participate in building and iterating predictive and statistical models, helping shepherd them from prototype to production
- Help identify the key components in these complex metrics and turn them into language that allows them to be readily used in storytelling across ESPN platforms
- Engage consistently and thoroughly with external partners around dissemination of the team's metrics
- Identify trends and help the team react to news stories using the tools developed by the team
- Be engaged in the larger sports analytics community and stay current on the latest research in sports statistical analysis
Qualifications:
- A minimum of 3 years' experience with sports analytics or a bachelor's degree in a related field of study
- Some experience with predictive modeling, machine learning, Bayesian statistics, and trend analysis, with a primary focus on translating those models into reliable, production-grade code
- Demonstrated experience coding in R, Python, and SQL
- Experience in AWS cloud management
- Full availability for this position, which could include nights, weekends, and holidays
- Demonstrated ability to ensure accuracy of content
- Knowledge of the sports statistical analysis landscape
- Strong sports knowledge, both historical and current
Preferred Requirements:
- Degree in statistics, engineering, advanced mathematics, or a related quantitative field
- Experience developing and maintaining end-to-end modeling pipelines in a production environment, from experimentation through deployment
- Proficiency in R, particularly for statistical modeling and analysis
- Experience in general data wrangling, database development, and SQL coding
- Experience with sports betting markets and how betting data can inform modeling
- Experience writing production-quality code and collaborating via source control
- Experience developing and managing cloud computing environments
- Proven ability to translate sports analytics into compelling storylines
- Background in digital and/or television sports production
Required Education:
- Bachelor's degree or equivalent
Preferred Education:
- Statistics, engineering, advanced mathematics, or economics degree strongly preferred
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