You will own data analysis and modeling efforts to inform Rams marketing and guest experiences, turning insights into dashboards, data-driven recommendations, and scalable tools.

Build and refine data models for fan segmentation and marketing metrics
Translate findings for technical and non-technical audiences

Job Description

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

Marketing Team

Marketing Roles Posted (Last 30 Days)

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