Define and drive the search and shopping strategy for StreetEasy across web, iOS, and Android, from initial query through listing and building evaluation to finding “the one”.
Build personalized shopping experiences using smart defaults, targeted nudges, and AI-assisted exploration.
Own the property evaluation pages and experience, helping users navigate NYC-specific nuances like co-op policies and pricing.
Optimize the shopping journey, including browsing, comparing, saving, and sharing listings.
Lead the experimentation and deployment of AI-powered personalization and recommendation models, partnering with engineering and data science to translate behavioral signals into measurable improvements for search and discovery.
Balance innovation with the trust and accuracy StreetEasy's audience expects, ensuring new experiences meet high standards for data quality and reliability.
Requirements
6+ years of digital product management experience (3+ years focused on search, discovery, or content relevance in a dual-sided marketplace)
Deep technical expertise in search relevance, ranking, and AI/ML-powered personalization systems, defining requirements for core platform and experimentation infrastructure.
Fluency in managing behavioral data as a core product input that powers personalization and agentic systems.
Proven track record of optimizing complex consumer flows through rigorous A/B testing and experimentation, driving measurable outcomes from clear hypotheses.
Exceptional cross-functional leadership, consistently aligning Engineering, Design, Data Science, and business stakeholders through clear product vision and compelling storytelling.
Experience managing the tension between optimizing the organic user experience and successfully integrating advertising products without compromise.
Analytical, structured thinker who thrives in ambiguity and moves quickly from insight to execution.
Tech Stack
Android
iOS
Benefits
equity awards based on factors such as experience, performance and location