The Senior Sports Data Scientist will serve as a technical leader in designing and implementing advanced predictive models and metrics that power ESPN's analytics products and storytelling.
Requirements
- Minimum 5 years of experience in data science, machine learning, or quantitative analytics, with demonstrated expertise in sports analytics preferred
- Advanced proficiency in Python or R for statistical modeling and machine learning
- Expert-level SQL skills and experience with database systems
- Deep understanding of statistical methods including regression analysis, time series forecasting, Bayesian inference, and causal inference
- Proven track record of deploying machine learning models to production and monitoring their performance
- Experience with cloud platforms
- Experience with version control (Git) and software engineering best practices
Responsibilities
- Design and implement advanced machine learning models and statistical algorithms to predict player and team performance, including pre-game and in-game predictions
- Apply modern techniques including deep learning, Bayesian methods, ensemble models, and reinforcement learning to solve complex sports analytics problems
- Leverage AI technologies to enhance analytics capabilities and create innovative solutions for sports player and team evaluation
- Collaborate with engineering teams to deploy models at scale, ensuring robust performance in production environments
- Transform complex statistical findings into clear, actionable insights that enhance storytelling across all ESPN platforms
- Partner with product and content teams to identify high-impact opportunities for analytics integration
- Mentor junior data scientists and establish best practices for code quality, model validation, and documentation
Other
- Serve as a technical leader
- Translate sophisticated analyses into compelling narratives that resonate with diverse audiences
- Manage projects
- Partnering with engineering, product, and content teams
- Present findings to senior leadership and external stakeholders, adapting communication style for technical and non-technical audiences
- Stay current with academic research and industry trends in sports analytics, machine learning, and data science
- Contribute to the team's technical strategy and help evaluate emerging technologies and methodologies
- Strong communication skills with ability to explain complex technical concepts to diverse audiences
- Demonstrated passion for sports with working knowledge of major sports leagues, players, teams, and statistical trends
- Ability to work in a fast-paced environment with competing priorities and tight deadlines
- Full availability for this position, including occasional nights, weekends, and holidays during major sporting events
- Schedule Flexibility: This role requires flexibility to work outside standard business hours ahead of and during major sporting events, playoffs, and breaking news situations. Occasional weekend and holiday work will be necessary to support live productions and time-sensitive analytics.
