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Known brand, metro location, generalist ML title, and broad production skill requirements increase applicant competition.
Core ML and production skills are transferable, but media-measurement methodology and survey expertise add domain specificity.
No explicit years but strong mandatory ML, production and data-engineering requirements.
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Develop and deploy scalable AI/ML measurement and planning solutions for media publishers, advertisers, and agencies.
Implement and maintain data pipelines and production-ready models in a cloud environment, ensuring reproducibility and quality.
Collaborate with cross-functional teams to validate, optimize, and communicate methodologies in cross-platform audience measurement research.
Experience in AI/ML model building and production software development, including deployment in cloud environments.
Ability to perform data cleaning, dimension reduction, and data integration for large-scale datasets.
Experience with programming and version control for production-quality code and documentation of methodologies.
Work Experience Required: Not explicitly mentioned in the JD.
A professional comfortable bridging data science, software development, and data engineering to build scalable AI/ML solutions.
Experience in media or audience measurement domains involving statistical modeling, trend analysis, and bias reduction.
Able to handle end-to-end data science projects including data exploration, production code maintenance, and research methodology communication.