The Football Information Season Associate will utilize data analysis, data visualization, statistical modeling, and other techniques to assist the club’s Football Operations department in evaluating league-wide trends and player-specific metrics by identifying key insights for decision makers.

This internship is temporary and would begin approximately June 2026 and will end approximately May 2027.   

ESSENTIAL FUNCTIONS:
The Season Associate position will have daily responsibilities including, without limitation, the following:

• Work with other members of the Football Information Department to create and maintain tools and resources for coaches, scouts, and other staff members within the front office.
• Analyze large quantities of football data to develop actionable insights for decision-makers.
• Utilize statistical programming, machine learning, and data visualization skills to complete various projects to help club better understand trends in both professional and college football.

NONESSENTIAL FUNCTIONS:

• Will accept other responsibilities and duties required by the supervisor consistent with the objectives and essential functions of this position. Such responsibilities shall be incorporated into the position description if they are ongoing.
• Must be motivated, reliable, and able to work independently or as part of a team.
• Maintain professionalism when communicating with internal and external contacts.
• Must be accurate and efficient with ability to meet deadlines.
• Must be detail oriented with strong organizational skills.
• Must have the ability to gather and analyze information skillfully and develop solutions quickly and effectively.
• Will adjust work schedule to meet departmental demands.
• Will keep appropriate information confidential.

QUALIFICATIONS/REQUIREMENTS:

• Bachelor’s degree in computer science, statistics, or relevant field required
• Experience working with a collegiate or professional sports team preferred
• Coursework in statistics and/or machine learning or equivalent experience
• Intellectual curiosity and enthusiasm for answering questions with data
• Ability to work with data programmatically using R and/or Python
• Proficiency in statistical modeling preferred