Product Owner (Recommendation Systems)

Accountabilities • Own the post-purchase customer journey, focusing on activation, matching, relevance, and the speed at which paying customers reach meaningful value.

• Optimize offer volume and recommendation quality so customers receive a relevant selection without being overwhelmed or underserved. • Improve the relevance and trustworthiness of recommendations and increase the number of relevant invitations reaching paying customers. • Increase the likelihood that new customers achieve a quality match during their first week. • Design and improve engagement mechanics such as gamification, nudges, reminders, and conversation reactivation features. • Analyze matching parameters across user segments and apply segmentation, personalization, and data enrichment to improve recommendation outcomes. • Identify bottlenecks and growth opportunities across the post-purchase journey using quantitative data, qualitative research, and product insight. • Translate product opportunities into clear, testable hypotheses with defined success metrics and measurable outcomes. • Partner with engineers, designers, analysts, and data/ML specialists to prioritize, develop, test, and launch product improvements. • Manage product requirements, priorities, and delivery timelines to ensure efficient and predictable execution. • Run A/B tests and other product experiments, analyze results and metrics, and iterate or scale solutions based on evidence. • Take end-to-end ownership of product outcomes, focusing on measurable impact rather than process for its own sake.

Requirements

• Hands-on B2C product experience, particularly in customer experience, customer journey design, activation, onboarding, or first-session experiences. • Experience working with discovery-driven products involving large volumes of offers, listings, or potential matches. • Practical understanding of search and feed relevance, matching systems, recommendation engines, personalization, or related product experiences. • Experience with segmentation, personalization, and enriching offers or listings with additional data. • Relevant experience in marketplaces, aggregators, dating or social discovery, real estate, classifieds, e-commerce with large catalogs, or other discovery- and recommendation-driven products. • Strong ability to formulate product hypotheses, define clear requirements, and establish measurable success criteria. • Proven ability to drive product delivery from idea through implementation and evaluation. • Experience designing and analyzing A/B tests and other product experiments. • Comfortable combining qualitative and quantitative research to understand customer behavior and validate product decisions. • Strong understanding of product metrics and the ability to identify meaningful growth opportunities from data. • Effective cross-functional collaboration skills, with experience working closely with designers, analysts, engineers, and data/ML specialists. • Results-oriented mindset with a strong sense of ownership and willingness to make decisions independently. • Comfortable working with changing priorities and ambiguity in a fast-paced product environment. • Clear, direct communication skills and a willingness to treat failures and experiments as opportunities for learning.