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AI Royalty Split Prediction Engineer

Audrey Fischer

Freelance · Job · Los_Angeles

About the role

We serve independent artists and small labels who lose real money every time a royalty split gets calculated wrong on a collaborative track. Fast-moving team, small problem-space, we need someone who ships clean models without a lot of process overhead. You'll build the model that predicts fair royalty splits based on contribution signals like stem separation data, writing credits, and historical splits on similar tracks. The impact shows up directly in artist payouts, and getting it wrong means real disputes between people who used to be friends.

Responsibilities

  • Build models predicting fair royalty splits from contribution signals
  • Incorporate stem separation and writing credit data
  • Validate predictions against historical negotiated splits
  • Flag low-confidence predictions for manual review
  • Document model assumptions for the artist relations team

Requirements

  • 1-2 years in applied ML, ideally in music or media
  • Comfortable with Python and scikit-learn
  • Interest in music industry royalty and licensing structures
  • Available for freelance, project-based engagement
  • Clear written communication for explaining model outputs

Benefits

  • Remote freelance engagement
  • Flexible project-based schedule
  • Potential for repeat engagements
  • Access to music industry contribution datasets

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Categories

data science & analytics AI Business, Marketing & Strategy

Skills

python sql pandas scikit-learn statistics

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Job Type

Freelance

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

data science & analytics AI Business, Marketing & Strategy

Skills

python sql pandas scikit-learn statistics

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