Job Description
Lead Scientist, Machine Learning Universal Music Group - 4.0 Santa Monica, CA Job Details Full-time $150,000 - $175,000 a year 9 hours ago Benefits Paid parental leave Paid holidays Health insurance Dental insurance Tuition reimbursement Paid time off Parental leave Vision insurance Loan assistance Qualifications Data-driven problem-solving Full Job Description 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 design, develop, and scale high-impact machine learning systems that directly support UMG's forecasting, automation, and strategic decision-making capabilities. You will translate ambiguous business problems into well-defined modeling approaches, lead complex modeling initiatives end-to-end, and serve as a technical authority within UMG's applied ML organization. You are both a deep individual contributor and a force multiplier for the broader team. Bring your VIBE:
Applied ML Leadership:
Own the design and execution of core machine learning initiatives across priority business domains. You will evaluate problem structure and data characteristics to determine when traditional ML, Generative AI, or deterministic approaches are most appropriate, in alignment with UMG's "right tool for the job" framework. Design, build, and productionize machine learning models across the full lifecycle—from feature engineering and training to deployment, monitoring, and retraining. You will proactively identify model degradation, concept drift, and regime changes driven by market or business shifts. Act as technical lead on complex modeling efforts, setting modeling standards and best practices while mentoring junior scientists. You will review modeling approaches for rigor, interpretability, and business relevance. Partner closely with Finance, Data, Product, and Engineering teams to integrate ML outputs into driver-based financial models, dashboards, and decision-support tools. You will help stakeholders understand why models move, not just that they move. Generative AI & Advanced Modeling:
Design and evaluate Generative AI use cases where unstructured data, language, or synthesis meaningfully improve outcomes. You will prototype, validate, and productionize LLM-based workflows with appropriate safeguards around accuracy, privacy, and IP protection. Ensure that GenAI systems are grounded in reliable data sources and integrated with deterministic or predictive models where appropriate, avoiding standalone "black box" deployments. Partner with Legal, Privacy, and Data teams to ensure all models meet UMG's standards for ethical use, explainability, and data lineage. You will help enforce strong data hygiene and documentation practices across the ML stack. Contribute to defining success metrics for ML initiatives and support ROI measurement through accuracy gains, operational efficiency, revenue lift, or risk reduction. Bring your VIBE:
MS or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field. 5+ years of hands-on experience building and deploying machine learning models for real-world business problems. Strong proficiency in Python and modern ML libraries (PyTorch, TensorFlow, Scikit-Learn; Transformers experience strongly preferred). Practical experience with Generative AI and LLMs, including prompt design, evaluation, and integration into production workflows. Experience deploying models in cloud-native environments, ideally within AWS (SageMaker, EC2, Glue). Ability to clearly explain modeling tradeoffs and results to technical and non-technical partners. Perks Playlist:
Join an entrepreneurial, global organization where authenticity, boldness, creativity, connection, drive, and insight aren't just values—they're how we work every day. Here are some of the ways we support you along the way (and just a few of the benefits we offer): Comprehensive medical, dental, and vision coverage Including 100% coverage for out-patient in-network mental health services Fertility coverage for eligible medical plan participants Wellbeing reimbursements for fitness classes, spa treatments, meal services, travel, and so much more (up to $720/year) Student Loan Repayment Assistance and Tuition Reimbursement 401(k) with 100% immediate vesting on the first 5% of your contributions, plus an additional UMG contribution A variety of ways to prioritize much-needed time away from work including: Flexible Paid Time Off (PTO) for exempt employees 3-weeks PTO for non-exempt employees 2-weeks paid Winter Break 10 Company Holidays (including Juneteenth and Wellbeing Day) Summer Fridays (between Memorial Day and Labor Day) Generous paid parental leave for every type of parent Check out our full overview of benefits on the Perks Playlist page of the career site. Disclaimer:
This job description only provides an overview of job responsibilities that are subject to change. Universal Music Group is an Equal Opportunity Employer We are an E-Verify employer in Alabama, Arizona, Georgia, Mississippi, North Carolina, South Carolina, Tennessee, and Utah. Please note, UMG is not enrolled in E-Verify in California and New York, and cannot support employment of candidates whose employer must enroll in E-Verify, for example candidates on STEM-OPT.
For more information, please click on the following links. E-Verify Participation Poster:
English / Spanish E-Verify Right to Work Poster:
English | Spanish Job Category:
Data, Analytics & Business Intelligence Salary Range:
$150k-$175k The actual base salary offered depends on a variety of factors, which may include, as applicable, the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. All candidates are encouraged to apply.
