Sports Data Scientist

Job Description

The ESPN Sports Analytics team is a multidisciplinary group within Business Development & Innovation where all members have a deep knowledge of sports, statistics, databases, coding, and storytelling. Combining best-in-the-industry data with advanced mathematics and statistical modeling skills, Sports 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 NFL, NBA, college football and college basketball. These products make fans better informed and help keep ESPN at the cutting edge of sports statistical analysis.

The Sports Data Scientist will be the lead architect in designing team and player performance metrics and their underlying framework. The Sports Data Scientist will work with the Analytics leadership team to define project timelines and delegate duties, as well as assisting in evaluating potential projects. The incumbent must demonstrate critical thinking about the execution of the projects and keep Analytics leadership informed of progress. Completing work on deadlines is a crucial requirement. A portfolio of successful analytics projects and metrics is necessary to be considered for this position. The Sports Data Scientist will have the skills to partner with other data scientists and developers as well as Content teams and Technology and Digital Product staffers on projects. Candidates need to have a deep understanding of Bayesian statistics and a background in constructing predictive models and complex formulas that explore new areas of analytics, ideally in sports.

But the role of the Sports Data Scientist doesn't end with the numbers. The person in this role will be required to turn this information into language that allows integration into storytelling across all ESPN platforms, including TV and digital. The Sports Data Scientist will tell stories in the most accurate way, using advanced analysis and matching the storytelling to the medium. Translating the complex into understandable language is a key component.

The Sports Data Scientist must demonstrate peer-to-peer leadership and the ability to have 1-2 direct reports, if necessary, and the incumbent must execute the requisite supervisory functions that entails.

Ideal candidates will possess the following traits:
• Meticulous attention to detail in striving for 100 percent accuracy
• The ability to thrive under deadlines
• The ability to work both independently on a project with little supervision and as part of a team
• Strong technical skills and the ability to understand ESPN's data structure
• Demonstrated excellence working with multiple departments to achieve a common goal
• Strong verbal and presentation skills
• Demonstrated ability to regularly produce ideas on areas of opportunity within performance analytics for ESPN

Responsibilities
• Use advanced mathematics and statistical modeling to develop sports performance metrics
• Help set the direction of the department by partnering with Analytics leadership to set project priorities
• Identify the key components in these complex statistics and turn them into language that allows them to be readily used in storytelling across ESPN platforms
• Work collaboratively through conflicts and gain support from internal project partners and stakeholders with various interests and priorities
• Support the department's training plan by contributing to the education and integration of Sports Analytics storytelling tools to folks across ESPN
• Collaborate with Analytics staffers and ESPN technology partners to write scripts, queries and code to transform data into automated metrics across our digital platforms and internal research tools
• Use strategic analytical approaches and techniques using data to answer sports questions

Basic Requirements
• 5 years' experience with sports analytics, or any equivalent combination of education and experience that provides the applicant with the knowledge, skills and ability to perform the job
• 5 years' experience constructing statistical models to explain or predict performance
• 5 years' experience in a programming language such as R or Python
• Strong knowledge in using SQL to query and modify data from databases
• A passion for sports and statistics; candidates need to have a working knowledge of players, teams and the rules of the games

Preferred Requirements
• Expert knowledge in at least one statistically relevant programming language, such as R or Python.
• Demonstrated portfolio of predictive modeling experience in sports, particularly utilizing Bayesian regression.
• Experience with machine learning or other artificial intelligence techniques.
• Deep understanding of the all major sports and the current state of data therein.
• Previously worked with and have a solid understanding of player tracking data within various sports.
• Strong understanding of sports gambling and fantasy, particularly around predictive player and team performance.
• Experience turning sports analytics into storylines

Basic Education
• College degree in statistics, engineering, mathematics, econometrics or a related field

Preferred Education
• Advanced college degree in statistics, engineering, mathematics, econometrics or a related field

var jobInfo = {

category: 'Data-Science-and-Analytics',

location: 'Bristol, Connecticut, United States; Town of Bristol, Connecticut, United States',

req: '7123323120210224',

}

Jobcode: Reference SBJ-r0zekj-3-21-231-245-42 in your application.