An Important Note about Wayfair's In-Office:
Please note that this is a hybrid role based in Toronto, and will require you to work in the office on Tuesdays, Wednesdays, and Thursdays.
Who We Are
At Wayfair, we believe everyone should live in a home they love. To make that a reality, we are looking for a Senior Product Manager for Content Recommendations to lead the evolution of how we surface inspiration and ideas to millions of shoppers.
This is a high-impact role where you will define how Wayfair uses lifestyle imagery, video content, and modular page layouts to create a cohesive, personalized discovery journey. You will own the "intelligence" that decides not just what a customer sees on our homepage, but sitewide and how that experience translates across our app, web, and outbound marketing communications.
What You’ll Do
Architect the Discovery Engine: Define and execute the roadmap for Wayfair’s content recommendation systems, focusing on the discovery of non-product content (lifestyle imagery, "Shop the Look" modules, and short-form video).
Visual & Video Personalization: Partner with AI/ML teams to leverage computer vision and LLMs to recommend the most relevant images and videos. You will ensure that a "Modern Farmhouse" enthusiast sees vastly different visual content than a "Mid-Century Modern" shopper.
Omni-Channel Continuity: Ensure a seamless "Storefront to Inbox" experience. You will collaborate with the Marketing and Communications teams to power personalized content recommendations within Email, Push Notifications, and Direct Mail.
Collaborate with Creative & Tech: Act as the bridge between our Creative/Content studios and our Data Science/Engineering teams to ensure our rich media assets are tagged, indexed, and surfaced effectively.
Experimentation at Scale: Drive a high-velocity A/B testing culture. You will move beyond simple conversion metrics to measure "inspiration," "dwell time," and "long-term brand affinity" driven by content.
5+ Years in Product Management: Proven experience in AI/ML products, with a specific focus on content discovery, feed ranking, or recommendation engines in a consumer-facing environment.
Deep Technical Fluency: Strong understanding of ranking systems and recommendation architectures. Experience with Visual AI, Computer Vision, or Video Recommendation systems is a significant advantage.
Modular Thinking: Experience managing "platform-style" products where you are ranking diverse types of content (e.g., banners vs. videos vs. AI Content vs. UGC) within a single UI.
Strategic Storytelling: Ability to simplify complex ML concepts into a clear vision for creative stakeholders and executive leadership.
Data-Driven Empathy: You can look at a spreadsheet of engagement metrics and see the human shopper behind it, using data to build experiences that feel assistive, not intrusive.
Education: Bachelor’s degree in Computer Science, Engineering, or a related quantitative field.
Key Success Indicators
Increased Engagement: Growth in click-through rates (CTR) on lifestyle content and video views.
Relevance Metrics: Improvement in "Helpfulness" scores and a reduction in "bounce rates" on discovery surfaces.
Cross-Channel Lift: Increased conversion and retention originating from personalized content in email and push notifications.
Model Velocity: Shortening the time from "content creation" to "personalized recommendation" through automated tagging and ranking frameworks.
Gym/Fitness discounts
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