Sports Data Engineer

Job Posting Title:

Req ID:

Job Description:

The Sports Data Engineer will assume a role within the team as a developer by setting forth a vision for the modernization of its tech stack, helping guide and mentor more junior members of the team, and serving as a key developer across many of the team’s new and existing metrics. This will include gathering, wrangling, and verifying data, creating advanced statistical models, and writing code to execute those models. Candidates need to have a deep understanding of internal analytics metrics and be able to communicate results both internally and externally. 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 an 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.

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.

Responsibilities:

• Develop data requirements for new metrics and help establish a technical methodology for production execution
• Write optimized, production-quality code to transform data into automated metrics across ESPN platforms and internal research tools
• Help identify the key components in these complex formulas 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 be aware of the latest sports statistical analysis research

Qualifications:

• A minimum of 3 years’ experience with sports analytics or a bachelors’ degree in a related field of study
• Some experience with predictive modeling, machine learning, Bayesian statistics, trend analysis, and other data analysis techniques
• Demonstrated experience coding with programming languages such as 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
• A knowledge of sports statistical analysis in the marketplace
• Strong sports knowledge, both historical and current

Preferred Qualifications:

• Statistics, engineering, advanced mathematics degree
• Experience in the R Programming language
• Experience in general data wrangling, database development, and SQL coding
• Experience with sports betting
• Experience writing production-quality code and collaborating via SCM
• Experience developing cloud computing environments
• Experience turning sports analytics into storylines
• Experience in digital and/or television sports production
• Strong understanding of sports betting and how betting markets work

Required Education:

• Bachelor's Degree in a related field

Preferred Education:

• Statistics, engineering, advanced mathematics or economics degree strongly preferred

#ESPNMedia

Job Posting Segment:

Job Posting Primary Business:

Primary Job Posting Category:

Employment Type:

Primary City, State, Region, Postal Code:

Alternate City, State, Region, Postal Code:

Date Posted: