We are UMG, the Universal Music Group. We are the world’s leading music company. In everything we do, we are committed to artistry, innovation and entrepreneurship. We own and operate a broad array of businesses engaged in recorded music, music publishing, merchandising, and audiovisual content in more than 60 countries. We identify and develop recording artists and songwriters, and we produce, distribute and promote the most critically acclaimed and commercially successful music to delight and entertain fans around the world. How we LEAD:To support the development, testing, and deployment of machine learning models that improve UMG’s forecasting accuracy, automation capabilities, and analytical insight. You will work closely with senior scientists to turn data into reliable, well-documented models while building strong foundations in applied machine learning best practices. How you’ll CREATE:Model Development & Analysis:Develop, train, and evaluate machine learning models under the guidance of senior team members. You will contribute to feature engineering, model experimentation, validation, and performance analysis across structured and unstructured data sets. Assist in implementing and maintaining models in production environments, including monitoring performance and retraining workflows as data evolves. Conduct exploratory data analysis to identify patterns, anomalies, and opportunities for odelling improvement, translating findings into clear technical summaries. Applied Learning & Tooling:Contribute to traditional ML and Generative AI projects, gaining hands-on experience with predictive models, NLP workflows, and automation pipelines. You will learn when different odelling approaches are appropriate and how they fit into broader business systems. Write clean, well-documented code and support reproducible experimentation through version control, experiment tracking, and model documentation. Collaboration & Governance:Work closely with data engineers, analysts, and senior scientists to ensure models are grounded in high-quality data and aligned with business needs. Support the preparation of model outputs and insights for downstream consumption in dashboards, reports, or financial models. Follow established best practices around data hygiene, privacy, and ethical model use. You will learn how governance and compliance considerations shape real-world ML systems. Bring your VIBE:BS or MS in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field .–3 years of experience applying machine learning techniques through coursework, research, or professional experience. Proficiency in Python and familiarity with common ML libraries (Scikit-Learn, Py. Torch or Tensor. Flow). Foundational understanding of machine learning concepts, including model evaluation, overfitting, and feature engineering. Curiosity, strong analytical instincts, and a desire to learn how ML creates real business value beyond model accuracy.