Data Analyst
Harrison, NJ, United States
Red Bull
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The New York Red Bulls are one of 30 Major League Soccer (MLS) teams. RBNY, one of the ten charter clubs of MLS, has competed in the league since its founding in 1996. The Red Bulls play home matches at Sports Illustrated Stadium (SIS) in Harrison, New Jersey. The three-time MLS Supporters' Shield Winners are owned by the Austrian beverage company Red Bull, for which the team is named. The New York Red Bulls offer one of the nation's premier youth soccer development programs, from local soccer partnerships across New York and New Jersey to Regional Development Schools and the Red Bulls Academy teams.
Purpose of this Job
We are seeking a talented and highly motivated Data Analyst to join our team at the New York Red Bulls (Business Strategy and Analytics). In this role, you will work closely with multiple commercial departments (Ticketing, Sponsorships. Operations, Marketing, Finance, IT) to gather, analyze, and interpret data to drive decision-making and optimize business strategies. This is an excellent opportunity for someone who is passionate about data and its impact on business performance in a fast-paced, dynamic environment.
Job Description
- Collect, clean, and analyze large sets of data from various business operations, including ticket sales, marketing campaigns, merchandise, fan engagement, and digital platforms.
- Design, implement, and maintain ETL (Extract, Transform, Load) processes to ensure accurate and efficient data flow from source systems into our data warehouse.
- Work with the IT to manage and optimize the data warehouse architecture and ensure data is properly structured and accessible for business analysis.
- Develop and maintain reports, dashboards, and data visualizations to track key performance indicators (KPIs) and provide actionable insights to business leaders.
- Work cross-functionally with teams such as marketing, sales, finance, and operations to support data-driven decision-making and business performance improvement.
- Conduct ad-hoc data analysis and provide data-driven recommendations for strategic initiatives.
- Assist in the development of predictive models and advanced analytics to optimize revenue generation, customer acquisition, and retention strategies.
- Identify trends, patterns, and opportunities for improvement to enhance overall business performance.
- Present findings in a clear and concise manner to both technical and non-technical stakeholders.
- Ensure data integrity, accuracy, and compliance across multiple systems and sources.
Qualifications
- Bachelor's degree in Data Science, Statistics, Economics, Business, or a related field.
- 2+ years of experience in data analysis or a related field, preferably in a business or sports environment.
- Proficiency with data analysis tools (e.g., SQL, Excel, Python, R, Tableau, Power BI).
- Proficiency in data warehouse management and experience with ETL processes (e.g., using tools such as SQL Server Integration Services, Talend, Apache Nifi, or similar).
- Strong understanding of data visualization and reporting techniques.
- Experience with statistical analysis, forecasting, and predictive modeling.
- Excellent communication skills, with the ability to present complex data insights in an accessible and actionable format.
- Strong attention to detail and ability to work independently.
- Knowledge of the sports and entertainment industry is a plus, but not required.
Additional Information
Due to the cyclical nature of the entertainment industry, the employee may be required to work varying schedules to reflect the business needs of the company.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Classification Data analysis Data visualization Data warehouse Economics ETL Excel Finance KPIs NiFi Power BI Predictive modeling Python R SQL Statistics Tableau Talend
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