Personalization Product Lead

Faire•San Francisco, CA

6d•$220,000 - $302,500•Hybrid

About The Position

Faire is a technology wholesale platform that connects independent retailers with products and brands using technology, data, and machine learning. The Personalization Product Lead owns the recommendation and ranking systems that shape retailer discovery across Faire’s home page, brand catalogs, and other product surfaces. The role begins with end-to-end ownership of Personalization and is expected to grow into a product lead role for the area after the successful candidate builds context, establishes how the scope should be divided, and hires a second Personalization Product Manager. The role combines technical product leadership with customer and business impact. The lead works closely with machine learning engineers, data science, engineering, and other product partners to set strategy and roadmaps, prioritize opportunities, and improve retailer experiences. The position is hybrid, with employees currently expected in the office three days per week and flexibility to work remotely for up to four weeks per year.

Requirements

At least 8 years of product management experience.
Experience owning a technical product area at senior individual-contributor or Staff level.
Direct experience shipping recommendation, ranking, or personalization systems.
Strong business judgment and a track record of making difficult prioritization decisions across stakeholder teams to deliver ambitious goals.
Experience dividing execution responsibilities with partner teams on shared goals, including defining ownership and aligning roadmaps.

Nice To Haves

Prior people-management experience.

Responsibilities

Own the Personalization roadmap and strategy end-to-end, covering recommendation and ranking systems across retailer discovery surfaces.
Build an understanding of retailer needs, discovery behaviors, and marketplace dynamics; use qualitative and quantitative research to identify opportunities and frame actionable problems.
Partner directly with machine learning engineers on model and system tradeoffs and improvements.
Co-create roadmaps with data science, engineering, and product partners, coordinating algorithm and engineering work to deliver customer and business impact.
Prioritize among collaboration and impact opportunities presented by other teams.
Be accountable for ambitious goals visible to senior company leadership.
Build credibility with senior leadership as an expert on Faire’s business and the effects of its algorithms on customers and the business.
Serve as a product leader for ambiguous, high-stakes problems in Discovery algorithms.
Improve how product and data science teams work together, particularly as AI changes their day-to-day partnership.
Determine how Personalization’s scope should be split, then help hire and onboard a second Product Manager.