Faire Staff Product Manager at Faire leads development of search algorithms to improve retailer product discovery. The role combines data science, marketplace strategy, and execution to drive algorithmic improvements.
Responsibilities
The Discovery pillar's mission is to make it easy and delightful for retailers to find brands and products their customers will love. This role will own development of our algorithms powering search, the largest discovery surface by order volume.
This role sits at the intersection of data science, marketplace strategy, and execution. You'll work closely with a world-class data science team to define goals, drive analytical clarity, and maintain the execution velocity that lets us keep improving these systems.
This is not a traditional PM role. We are looking for someone with deep analytical DNA — from a strategy & analytics, quantitative finance, or data science background. Prior product management experience is not required.
Develop and execute on a strategy that takes our search algorithms to the next level
Own a product roadmap for one of our search algorithm areas (such as ranking, retrieval, or query understanding) that is analytically grounded, clearly prioritized, and connected to business outcomes.
Direct the analytical work of the pod — working alongside dedicated strategy & analytics and data science partners to identify novel opportunities, diagnose root causes of failure modes, interpret outputs, and translate findings into clear priorities
Build trusted partnerships across ML Platform, Discovery Infrastructure, and adjacent Search and Personalization teams — managing team bandwidth while delivering on shared goals
Represent the team's strategy and progress to leadership, connecting algorithmic work to marketplace outcomes with analytical confidence.
Qualification
Execution rigor across complexExperience in searchSan FranciscoWhy you’ll love working at Faire
Required
Bachelor's degree or equivalent experience
5+ years of experience in a highly analytical role — such as strategy & analytics, quantitative finance, applied data science, or hands-on analytical consulting (e.g., economic consulting, or implementation-focused consulting with deep data and modeling work). We are open to candidates without prior product management experience who bring the right analytical depth and business judgment
Deep comfort working in data — you independently generate insights by knowing how to slice and frame analytical questions, and could hold your own sparring with data scientists on methodology and interpretation
Strong goal definition skills — you translate ambiguous business objectives into crisp, unambiguous goals, and catch misalignment early
Execution rigor across complex, multi-dependency work — you run a tight operation across many moving parts and proactively unblock bottlenecks
Marketplace business intuition — you reason about algorithmic decisions in aggregate terms (conversion, reorder rate, revenue impact) and understand two-sided marketplace tradeoffs
ML/DS partnership fluency — you don't need to build models, but you understand algorithmic system architecture well enough to ask the right questions and communicate credibly with highly technical counterparts
Experience in search, recommendations, or ads at a tech company is a plus
San Francisco, CA: The pay range for this role is $188,000 - $258,500 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors, including transferable skills, work experience, market demand, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
