Responsibilities

• Set the product strategy for Wayfair’s next generation MarTech platform, owning a 12–18 month portfolio strategy that connects company and Marketing priorities to measurable outcomes across revenue, profitability, and efficient growth.
• Turn complex, ambiguous marketing challenges into clear product opportunities. Define the problems that matter most, establish measurable outcomes, and translate them into a cohesive roadmap across the platform.
• Partner with channel leaders to unlock new growth opportunities. Work closely with Marketing leads as they expand into new and emerging channels, helping shape channel strategy, identify the capabilities required to win, and ensure Wayfair’s technology and data foundations are ready to scale investment successfully.
• Shape how Wayfair measures the true impact of $1B+ in marketing investment. Own the vision and roadmap for our marketing measurement and attribution ecosystem—including MMM, MTA, geo and customer-level incrementality testing, clean rooms, and the data products that power investment decisions.
• Build measurement products marketers trust and use. Partner deeply with Applied/ML Science and Data Engineering to develop and evolve models, data pipelines, and product experiences that turn sophisticated measurement into actionable decisions.
• Build platforms, not point solutions. Design scalable measurement and decisioning capabilities that can power multiple channels, regions, and use cases while creating a consistent foundation for how Wayfair evaluates marketing performance.
• Make rigorous experimentation dramatically easier and faster. Evolve self-service experimentation across geo, audience, bidding, and other marketing tests so teams can answer more questions independently without sacrificing scientific rigor.
• Connect experimentation directly to action. Create intuitive, end-to-end workflows spanning experiment design, execution, measurement, and readouts—making it easier for marketers to turn learnings into better investment and optimization decisions.
• Reimagine marketing workflows for an AI-first world. Apply systems thinking to how GenAI and advanced ML can transform the way marketers, PMs, and scientists build campaigns, design experiments, measure impact, allocate spend, and optimize performance.
• Turn AI from experimentation into scaled capability. Identify the highest-impact opportunities for AI—from automated campaign optimization and generative experiment design to smarter decisioning and guardrails—and establish patterns that enable teams to adopt them quickly, safely, and effectively.

Requirements

• 10+ years of Product Management experience leading complex, data/ML/analytics platforms.
• Proven track record owning a portfolio or multi‑year problem space, with clear impact on revenue, profit, or marketing efficiency.
• Deep familiarity with:
• - Marketing measurement & attribution (MMM, MTA, lift testing, clean rooms).
• - Bidding & optimization systems for performance marketing.
• - Experimentation platforms
• - Large‑scale data products and ML‑driven decisioning systems.
• - Search, social, influencer, CTV channel management and optimization
• Strong quantitative intuition and comfort working with ML/Statistics partners; able to interpret experimental results and model outputs and turn them into product and investment decisions.
• Demonstrated ability to set vision under ambiguity, define clear success metrics, and make high‑quality trade‑offs across channels, systems, and investment options.

Preferred

• Preferred: Experience in ad‑tech, marketing technology, or performance marketing at scale, and prior ownership of measurement, attribution, experimentation, or bidding products.