Responsibilities

• AI Data Orchestration & Activation: Lead the translation of AI-driven data sources into coordinated omnichannel and field engagement strategies. Partner across Marketing, GCCI, BAI, and brand teams to orchestrate data activation and maximize business impact.
• GEO Analytics & Optimization: Own and evolve the enterprise GEO analytics framework across brands. Lead the GEO vendor partnership, establish GEO measurement standards, and translate audit findings into actionable recommendations.
• Measurement Strategy & Business Impact: Develop KPI frameworks and measurement plans for AI-enabled marketing initiatives. Integrate AI metrics into brand performance reporting and quantify the impact of AI capabilities on engagement, brand performance, and business outcomes.
• Experimentation & Performance Optimization: Establish test-and-learn approaches, including pilots, A/B testing, and incrementality measurement, to evaluate AI initiatives and inform scaling decisions.
• Future AI Capabilities & Partner Evaluation: Develop success criteria and measurement frameworks for future AI capabilities. Assess emerging AI platforms, data partnerships, and technologies based on data quality, scalability, measurement readiness, and commercial value.
• Lead development of AI measurement frameworks, KPI architectures, and reporting standards, integrating AI metrics into brand reporting and business reviews, including execution, leading, and lagging indicators.
• Partner with Marketing, GCCI, BAI, and brand teams to operationalize OpenEvidence and other AI-derived data sources, translating insights into coordinated omnichannel and field engagement strategies.
• Own the enterprise GEO analytics framework and partner with the GEO vendor to evaluate performance, identify opportunities, and drive optimization recommendations across brands.
• Design and evaluate pilots, A/B tests, incrementality studies, and other experimentation approaches to determine which AI capabilities should be scaled.
• Quantify the business impact of AI-enabled initiatives and translate findings into actionable recommendations for marketing leadership.

Requirements

• Doctorate degree and 2 years of Marketing, Analytics, Business Intelligence, Commercial Operations, or related experience
• OR Master’s degree and 4 years of Marketing, Analytics, Business Intelligence, Commercial Operations, or related experience
• OR Bachelor’s degree and 6 years of Marketing, Analytics, Business Intelligence, Commercial Operations, or related experience
• OR Associate’s degree and 10 years of Marketing, Analytics, Business Intelligence, Commercial Operations, or related experience
• OR High school diploma / GED and 12 years of Marketing, Analytics, Business Intelligence, Commercial Operations, or related experience

Preferred

• - Experience leading marketing analytics, measurement strategy, or commercial analytics initiatives.
• - Strong understanding of omnichannel marketing, customer engagement measurement, KPI development, and performance analytics.
• - Experience designing experimentation frameworks, including A/B testing, incrementality studies, and causal measurement approaches.
• - Familiarity with AI search, GEO, OpenEvidence, and emerging AI-enabled marketing capabilities.
• - Experience translating complex analytics into actionable recommendations and executive-level insights.
• - Experience evaluating new technologies, data partnerships, and capabilities to inform investment and scaling decisions.
• - Experience managing external vendors and analytics partners to deliver business outcomes.
• - Strong cross-functional collaboration and influencing skills within a matrixed organization.
• - Ability to connect performance metrics to commercial outcomes and business impact.
• - Excellent verbal and written communication skills.

Benefits

• - A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
• - Stock-based long-term incentives
• - Award-winning time-off plans
• - Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.