Back
Known analytics brand, metro location, and broad ML-plus-production skillset increases candidate competition.
Role needs specialized audience measurement and sampling methodology experience, limiting cross-industry transferability.
Requires multi-disciplinary ML, production software, and data engineering skills without explicit years, making filters moderately strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deploy AI and machine learning models for media measurement and planning solutions targeting publishers, advertisers, and agencies.
Implement and maintain production data pipelines and reproducible data science projects in cloud environments.
Collaborate with cross-functional teams to validate, optimize, and communicate methodologies involving data integration, bias reduction, and sampling.
Experience in AI/ML model development and software engineering for production environments.
Ability to handle end-to-end data science project lifecycle including data cleaning, dimension reduction, and evaluation of outputs.
Not explicitly mentioned: formal degree requirements or exact years of experience.
Not explicitly mentioned: explicit notice period or location constraints.
Equally skilled in machine learning model development and production-ready software implementation.
Familiar with methodologies in sampling analytics, bias reduction, and indirect estimation in audience measurement contexts.
Experienced in working with cross-functional teams to operationalize data science solutions in fast-paced, research-driven environments.