Director, Campaign Effectiveness

Meta
Menlo Park, CA +1 location

About the job

The Global Media Team at Meta focuses on growing brand sentiment across Meta's products and services globally. We deliver results by developing media strategies and executing campaigns across internal and external channels to increase people's engagement and connection to Meta’s brands. We're looking for an accomplished AI-native media leader to develop the people, processes, and tools that increase campaign effectiveness and improve execution through campaign management. This person will lead efforts to understand and optimize the drivers of channel effectiveness, create quality and execution improvements across internal and agency teams, partner to innovate ad products available to use and influence tool and analytics roadmaps.

Responsibilities

Lead the team responsible for assessing and improving channel and campaign effectiveness, developing frameworks to optimize performance across digital, social, programmatic, and traditional channels.

Define KPIs and measurement frameworks to track campaign effectiveness and efficiency; drive channel-level impact over time.

Oversee campaign level analytics and optimization approach with brand campaigns, including structured test-and-learn programs.

Leverage data to identify root causes of issues and develop product and process improvements.

Establish standardized workflows, templates, and quality control frameworks across campaign planning, execution, and measurement.

Develop resourcing approaches to increase accountability and oversight of live campaigns across internal and external platforms.

Identify opportunities and oversee the build of automation and AI-powered tools and capabilities to increase results.

Assess and implement AI media solutions within campaigns to improve effectiveness.

Drive adoption of new technologies and platforms with training and change management.

Monitor emerging technologies and industry innovations to maintain competitive advantage.

Present recommendations, progress, and results to senior leadership.

Build strong relationships with Measurement, MarTech, Data Engineering, Creative, and Insights & Analytics to improve campaign results.

Partner with external vendors and agency partners to design joint goals and roadmaps that deliver improved outcomes.

Establish agency vendor management processes, scorecards, and performance optimization playbooks.

Create campaign execution best practices, supporting collaboration with partners to improve campaign results.

Lead, and develop a high-performing team with a results-driven mindset and high accountability.

Foster an environment of innovation, continuous improvement, and operational excellence.

Establish career development pathways and competency frameworks for campaign-related roles.

Qualifications

Minimum

12+ years of media experience within marketing/advertising organizations

7+ years of management experience, including managing people managers

Leadership experience at a media company or agency

Experience overseeing marketing at global scale across a portfolio of products

Performance marketing and digital media expertise

Expertise with MarTech and executing programmatic campaigns

Experience designing AI agents and with AI-assisted workflows

Demonstrated analytical skills with experience translating data into strategic decisions

Applied knowledge of industry trends in media, tracking, analytics, and research

Proven track record of influencing cross-functional partners

Preferred

Bachelor's degree

Experience working in-house at a consumer company

Experience working and thriving in a self-starter, fast-paced and changing environment

Experience leading in a complex, cross-functional organization across a portfolio of brands

Digital-first approach to solving complex brand and product challenges

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies