About this role

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 owns a product roadmap for one of our search algorithm areas — ranking, retrieval, or query understanding — 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, get into the weeds of the data, and maintain the execution velocity that lets us keep improving these systems.

What you'll do

• Own a roadmap for your search algorithm area that is analytically grounded, clearly prioritized, and connected to business outcomes such as retention, reorder rate, and buyer conversion.
• Direct the analytical work of your pod — partnering with dedicated strategy & analytics and data science partners to identify opportunities, diagnose root causes of failure modes, interpret outputs, and turn findings into clear priorities.
• Refine the offline and online metrics that help us understand the retailer's search experience and the performance of each system component.
• Run a tight operation across many moving parts — ML platform dependencies, retrieval/ranking coupling, feature engineering cycles, model architecture changes — and proactively unblock bottlenecks.
• Build trusted partnerships across ML Platform, Discovery Infrastructure, and adjacent Search and Personalization teams, managing your team's bandwidth while delivering on shared goals.
• Represent your team's strategy and progress to leadership, connecting algorithmic work to marketplace outcomes.

Qualifications

• Bachelor's degree or equivalent experience
• 4+ years of product management experience at a high-growth tech company, or 5+ years as a data scientist or machine learning engineer with 1-2 years transitioned into a product management role.
• 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
• You are relentlessly resourceful and comfortable executing with limited information and ambiguity
• Experience in search, recommendations, or ads at a tech company is a plus

Salary Range

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.