✦ Luna Orbit — AI & Machine Learning

Untitled Position

at Company

Unknown Posted March 29, 2026
Type Internship
Experience intern
Exp. Years 0
Education Graduate student in software or machine learning
Category AI & Machine Learning

Internship role focused on leveraging machine learning and data science to improve fan engagement and personalized marketing at Live Nation Entertainment.

  • Work on Automated Fan Engagement and Targeting Engine
  • Improve customer acquisition capabilities
  • Leverage large data sets and algorithms
  • Collaborate with Recommendations, Analytics, Marketing Automation teams
  • Research and evaluate tech tools

Work involves using Spark, Scikit-Learn, Pandas, AWS, and advanced AI technologies including generative AI and large language models to develop personalized fan experiences and marketing platforms.

The ideal candidate is a graduate student with strong curiosity and passion for data science and machine learning, experienced with Spark, Scikit-Learn, Pandas, and AWS. They should be motivated, innovative, and eager to work on large datasets and AI-driven personalization projects in a live entertainment context.

SparkScikit-LearnPandasAWSAmazon Web Servicesmachine learning
generative AIlarge language modelsLLMs
SparkScikit-LearnPandasAWSAmazon Web Servicesmachine learning
SparkScikit-LearnPandasAWSAmazon Web Servicesgenerative AIlarge language modelsLLMsmachine learning
curiosityinnovationforward thinkingresourcefulnessentrepreneurial spiritmotivationpassion
Industry Entertainment / Live Events
Job Function Develop machine learning solutions to enhance personalized marketing and fan engagement
Role Subtype ML Engineer
Tech Domains Amazon Web Services, Spark, Scikit-Learn, Pandas, Python
Marketing Data Science InternSparkScikit-LearnPandasAWSAmazon Web Servicesgenerative AIlarge language modelsLLMsmachine learningdata sciencecustomer acquisitionpersonalized communicationcollaborative filteringAI-driven personalization

Graduate student status in software or machine learning, Experience with Spark, Scikit-Learn, Pandas, and AWS

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