Responsibilities

• Analyze data from a variety of sources (e.g., ticketing, merchandise, digital engagement, CRM, surveys) to uncover trends and insights.
• Assist in building dashboards, reports, and visualizations using tools such as Excel, Power BI, or Looker Studio.
• Help structure and collect data to build tools and framework that feed into our data lake
• Apply data science and machine learning from an explorative and analytical angle; take initiative in reviewing marketing and business materials for ways to optimize future efforts, providing actionable, data-driven support for your recommendations
• Develop advanced data models
• Support business and team with your knowledge in data science, machine learning, AI, and APIs
• Leverage your experience to create data-driven models to enhance the Rams’ targeted marketing efforts, including customer lifetime value, churn predictions, degrees and shifts of fandom, purchase motivators, attitudinal/behavioral clusters, and more
• Support market research efforts (quantitative and qualitative), including survey creation, data cleaning, and synthesis of findings.
• Translate analytical findings into digestible, actionable insights for both technical and non-technical audiences.
• Collaborate with cross-functional teams to support business needs.

Requirements

• Demonstrated previous experience in statistical models, analysis, predictions, and algorithms for marketing purposes along with the software needed to complete these projects (Python, R)
• Have completed or working on completion of a bachelor’s degree in related field required (Business, Marketing, Analytics, Statistics, Mathematics, or similar)
• Experience with relational databases and data extraction software (e.g. SQL, SAS, Q, etc.)
• Experience with common reporting software (e.g. Tableau, Power BI, Domo, etc.)
• Experience with common digital analytics tools (e.g. Adobe Analytics, Google Analytics, etc.) preferred
• Experience working within large datasets to compile fan/customer segmentation schemas and segment-level insights
• Experience working extracting, cleansing, and formatting customer audiences for analytical purposes