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Über
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
#ESPNMedia
Job ID:
10145511
Location:
Bristol,Connecticut
Job Posting Company:
ESPN
ESPN Productions, Inc. is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.
Sprachkenntnisse
- English
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