2026 Internship, Fall - Data Science

Red Bull New York (“RBNY”) are one of 30 teams in Major League Soccer (MLS) and one of the league’s ten original charter clubs. Founded in 1996, RBNY has competed in MLS since its inception. RBNY’s First Team plays its home matches at Sports Illustrated Stadium in Harrison, New Jersey and its Second Team plays its home matches at Montclair State University. RBNY are owned by the Austrian beverage company Red Bull GmbH, after which the team is named.

RBNY’s First Team is a three-time MLS Supporters’ Shield winner and a two-time Conference Champion, while the Second Team is the 2025 MLS NEXT Pro Champion. RBNY also operates one of the nation’s premier youth soccer development programs, spanning local partnerships across New York and New Jersey. RBNY’s Academy is ranked among the top development organizations in the country.

Purpose of this Internship

During your time interning at the New York Red Bulls, you will learn how to apply your knowledge of data science, computer science, and mathematics to help multiple facets of a professional soccer team. You will assist multiple departments – including scouting, match analysis, and player development while aiding various processes including data cleaning, databasing, and software building.

This is an unpaid, for credit internship (proof that you will receive credit is required).

Communication skills in an elite sporting environment

Ability to foster a data-driven culture

How to create new Key Performance Indicators across a multitude of different departments

How to create algorithms and processes in an elite sporting environment

Proficient in R / SQL

Proficient in Microsoft Office Suite

Experience with Web Scraping

Excellent Communicator

In a Mathematics, Data Science, or Computer Science Program

Because of the cyclical nature of the entertainment industry, your assigned hours may vary to reflect our needs (includes nights and weekends).

Red Bull New York is an equal opportunity employer and we will not discriminate against any employee or applicant for employment because of age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality or any other classification protected by law.