Meta is seeking a Data Analyst to own and scale the analysis and technical infrastructure that powers communications measurement at Meta. In this role, you will be the dedicated technical lead for our press monitoring infra - including data pipelines, front-end tooling, AI-driven classification systems, and reporting tools that Comms teams rely on daily. The ideal candidate has a strong technical and analytical background who can bridge media domain expertise with production-grade execution. You won't just analyze and interpret data - you'll build and maintain the systems that produce it. You'll own pipelines end-to-end (ingestion through reporting), develop and improve front-end interfaces, implement AI-driven features, and ensure data quality at scale. Communications experience is a plus.
Responsibilities
Own and evolve the technical infrastructure powering our press measurements
• Design, build, and maintain front-end interfaces and dashboards that enable Comms teams to monitor media coverage, track campaigns, and surface insights in real-time
• Develop and maintain back-end data pipelines and integrations that ensure data accuracy, reliability, and scalability as monitoring expands globally
• Build and improve AI-driven features - including classification, relevance scoring, and automated reporting - and implement human-in-the-loop QA processes that keep AI outputs trustworthy
• Partner closely with Data Engineering teams to iterate on measurement methodologies, improve AI performance, and expand platform capabilities
• Debug production systems, manage data quality incidents, and ensure reporting continuity for stakeholders across Communications
• Identify opportunities to automate routine workflows, increase efficiency, and reduce manual overhead through new tooling and AI integration
• Contribute to the team's long-term technical strategy as the organization builds up its technical expertise and capabilities
Minimum Qualifications
• 6+ years of experience in data science, analytics engineering, or a related technical field with hands-on development work
• Strong proficiency in object-oriented programming and languages for data analysis (e.g., Python, SQL, R)
• Demonstrated ability to work across the stack - from data infrastructure and pipeline reliability to user-facing interfaces and reporting
• Experience leveraging AI/ML models in production workflows (e.g., text classification, NLP, relevance scoring)
• Experience communicating technical decisions and trade-offs to non-technical stakeholders (e.g., written summaries, presentations, documentation)
Preferred Qualifications
• Demonstrated ongoing AI skill development (e.g., prompt engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with AI-driven automation - building systems that combine model outputs with human-in-the-loop quality assurance
• Experience in building or maintaining internal tools and applications used by non-technical teams
• Experience with front-end development or data application development (e.g., internal tools, dashboards, web applications)
• Experience in communications measurement, media analytics, or press monitoring (earned media, sentiment analysis, message pull-through)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Track record of owning complex technical systems end-to-end with minimal oversight
• Advanced degree in computer science, data science, statistics, or a related quantitative field
• Experience building and maintaining data pipelines (ingestion, transformation, and orchestration) at scale
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
