Job Description
The Custom Media Analytics Delivery team sits within Nielsen's Commercial organization and functions as an incubator for new innovative products. We leverage existing Nielsen datasets to build custom solutions that don't yet exist in Nielsen's standard product portfolio. That means taking raw, often messy datasets from across Nielsen's ecosystem and turning them into something a client can actually use — which requires knowing the data deeply, modeling it correctly, and moving fast. What You'll Do Design and build new measurement products by combining Nielsen datasets across National and Local linear TV, Streaming, Audio, and Digital — understanding the weighting rules, projection logic, and methodology differences that make cross-dataset work hard to get right Develop statistical and machine learning models that extend or adapt Nielsen methodologies to answer questions that standard products can't address Write production-quality SQL, Python, and PySpark to extract, transform, and model data from Nielsen's cloud data environment Build reusable data pipelines and ETL workflows that allow custom solutions to be delivered repeatably rather than rebuilt from scratch each time Use AI tools actively — to validate models, accelerate pipeline development, stress-test logic, and compress the time between concept and delivery Translate stakeholder requests into well-scoped analytical problems, push back when the ask is unclear, and deliver with clear documentation of methodology and assumptions Collaborate with Research, Commercial Sales, and Client Insights teams; communicate complex model decisions in plain language Nielsen & Media Research Knowledge 3+ years working directly with Nielsen datasets (TAM, DAR/N1Ads, DCR, Audio, or similar) with hands-on knowledge of Nielsen's weighting, projection, and audience estimation methodology Proven ability to merge and reconcile multiple Nielsen data sources, navigating differences in sample design, universe estimates, and reporting
