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Metro location, popular AI/ML title, and broad production and research skillset increase applicant competition.
Core ML and data engineering skills are transferable, but Nielsen-specific media measurement and sampling increase domain sensitivity.
No explicit years but strong production ML, cloud, and methodology requirements imply moderate filtering.
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Develop and deploy AI/ML models and data pipelines for media measurement and planning solutions used by publishers, advertisers, and agencies.
Identify AI opportunities in projects, implement machine learning models, and support end-to-end reproducible data science workflows in production environments.
Collaborate cross-functionally to validate, optimize, and communicate data science methodologies and research findings, including addressing quality issues and maintaining documentation.
Experience in AI/ML model development and production software deployment, especially in data science projects.
Familiarity with data engineering practices, cloud-based production deployment, and software development best practices.
Work Experience Required: Not explicitly mentioned in the JD
Educational qualifications or specific degree requirements: Not explicitly mentioned in the JD
Comfortable working at the intersection of data science, sampling analytics, software development, and data engineering.
Experience with productionizing machine learning models and managing data pipelines in cloud environments.
Capable of communicating complex methodologies and collaborating effectively with cross-functional teams to support continuous project development and quality assurance.