Sr. Data Scientist / Member Technical Staff II at TheNielsenCompany

We are seeking an experienced MTS 2 with a Data Science or Machine Learning background and 4+ years of experience to join our Ads AI team within Gracenote — a Nielsen Company. You will design and build intelligent data services that expose Gracenote's entertainment metadata to agentic AI systems for transparent, privacy-compliant CTV advertising targeting. Working at the intersection of data science and production engineering, you will ship ML-powered features as real-time services consumed by AI agents via the Model Context Protocol (MCP). Responsibilities • Design, build, and maintain the Ads MCP Server — exposing Gracenote's advertising metadata as structured tools and resources that AI agents can discover and invoke. • Model and structure advertising data — define schemas, taxonomies, and retrieval strategies that make content metadata (genre, mood, brand safety, program attributes) useful for agentic ad targeting workflows. • Develop ML-powered features — build models for content classification, segment recommendation, similarity matching, and contextual relevance scoring. • Integrate with agentic AI workflows — work with LangGraph/LangChain-based orchestration to enable multi-step reasoning over advertising data. • Optimize real-time data retrieval — ensure segment lookups and metadata queries meet latency requirements for programmatic bid-time decisions. • Design prompts and structured output schemas that help LLMs reason effectively about advertising metadata. • Analyze and improve data quality — identify gaps in metadata coverage, propose enrichment strategies, and validate model outputs against ground truth. • Collaborate with data scientists, analysts, and engineers to implement and operationalize models and algorithms. • Identify and drive process improvements: automating manual processes, optimizing data delivery, improving model evaluation pipelines. • Create and maintain comprehensive technical documentation. • Mentor junior engineers and provide technical leadership on ML and data-related decisions.