Product Manager, Wayfair
Personalization and Fraud
$126.5-137.5k
+ Restricted stock units
More information about location
3 days a week in office
A global online homeware marketplace
Be an early applicant
A global online homeware marketplace
1001+ employees
Be an early applicant
$126.5-137.5k
+ Restricted stock units
More information about location
3 days a week in office
1001+ employees
Company mission
To help everyone, anywhere create their feeling of home.
Role
Who you are
- 2–4 years of experience in product management, ideally within data platforms, personalization, fraud/risk, or machine learning domains
- Familiarity with data modeling, distributed systems, and ML system design principles—you don’t need to write code, but you should be fluent discussing architectural trade-offs with engineers and scientists
- Strong product instincts with a platform-oriented mindset; you enjoy building foundational capabilities that unlock downstream value
- Clear, proactive communicator who can align cross-functional teams and stakeholders around shared objectives
- Experience managing third-party integrations (e.g., fraud vendors, personalization SDKs) and/or contributing to internal ML platform development is a plus
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field—or equivalent experience
What the job involves
- We are seeking a Product Manager to drive platform capabilities across Personalization and Fraud Detection, two high-impact domains that ensure customers see the most relevant offers while enjoying trusted and secure transactions
- You’ll work closely with engineers, data + ML scientists, and business stakeholders to deliver resilient, data-driven systems that scale with Wayfair’s global business
- Own the Platform Vision & Roadmap: Define and drive product strategy for personalization and fraud detection platform capabilities—powering everything from user-level content tailoring to real-time risk evaluation
- Design Scalable Data Systems: Partner with Engineering and Data Science to evolve core data pipelines, data models, and service architectures that support rules + ML-driven decisioning in real-time environments
- Collaborate Across Functions: Align with business partners (e.g., Fraud Ops, Loyalty/Personalization teams, Data Engineering, Finance) to translate goals into technical requirements and end-to-end solutions
- Leverage ML Principles Thoughtfully: Help operationalize model development pipelines, support inference and scoring services at scale, and prioritize features that make ML applications robust and extensible
- Drive Data Stewardship: Ensure data quality, system observability, and auditability across all personalization and fraud data surfaces
- Measure, Learn, Iterate: Define success metrics, monitor performance, and run structured experiments (e.g., A/B tests) in partnership with data science to validate improvements across user experience, model performance, and platform efficiency
- Champion Extensibility and Resilience: Balance rapid feature iteration with a vision for stable, reusable platform capabilities that can support future personalization and risk models across the Wayfair ecosystem
Our take
Wayfair emerged in the early era of eCommerce with a mission to revolutionize online shopping, offering customers a convenient platform to purchase goods. Today, it stands as one of the foremost global players in the online furniture delivery industry, boasting an impressive inventory of over 33 million products.
Renowned for its extensive product range and comprehensive service offerings, Wayfair distinguishes itself by providing an end-to-end customer experience, from browsing to doorstep delivery. Despite its prominence, the company faces profitability challenges attributed largely to expansion expenses. Nonetheless, its solid presence in the competitive online homeware sector solidifies its position as a key contender.
With ambitious global expansion plans, Wayfair remains committed to maintaining its leadership in the industry. As it aspires to become the ultimate destination for all home needs, its more recent ventures into physical retail represent significant strides toward this overarching goal.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-14% employee growth in 12 months
Company
Company HQ
Prudential / St. Botolph, Boston, MA
Leadership
Niraj Shah
(Co-Founder & CEO)Studied Engineering at Cornell University before co-founding Spinners, a Boston-based IT services company. Previously acted as Entrepreneur in Residence for Greylock and has served as CEO of Wayfair since co-founding the company in 2002.
Steven Conine
(Co-Founder)Co-founded Spinners before working for Operations at iXL. Conine also co-founded Pillar VC in 2016.
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