Product Owner

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Product Owner (Matchmaking) based in Italy.

As Product Owner (Matchmaking), you will shape the post-purchase customer journey, ensuring that paying users quickly discover relevant connections and experience meaningful matches. You will take end-to-end ownership of product improvements, from identifying opportunities and defining hypotheses to launching experiments and measuring results. Working at the intersection of product, data, engineering, and design, you will optimize activation, recommendation relevance, personalization, and customer engagement.

Your decisions will directly influence how users discover opportunities, build connections, and experience value during their first days on the platform. This is an opportunity to make a measurable impact within a globally distributed, remote-first environment focused on innovative social discovery products. If you combine analytical thinking, customer empathy, and a strong bias toward execution, you will have the autonomy to turn insights into impactful product outcomes.

Accountabilities

Own the Post-Purchase Customer Journey: Take end-to-end responsibility for the experience of paying customers, focusing on helping them achieve meaningful matches as quickly as possible. Identify friction points and opportunities to improve activation, engagement, and the time it takes users to experience product value.

Optimize Matching and Recommendation Relevance: Improve the relevance and quality of recommendations, ensuring customers receive an appropriate volume of options and develop trust in the suggestions presented to them.

Increase Meaningful Engagement: Develop strategies to increase relevant invitations and improve the likelihood that new customers achieve a quality match during their first week on the platform.

Drive Conversation Activation: Design and implement engagement mechanisms, including gamification, nudges, and reminders, that encourage users to return to conversations and build stronger connections.

Leverage Segmentation and Personalization: Identify the matching parameters that matter most to different customer segments. Use segmentation, personalization, and enriched offer data to improve recommendation quality and overall customer outcomes.

Identify Product Growth Opportunities: Analyze product metrics, customer behavior, qualitative feedback, and quantitative research to identify bottlenecks and prioritize opportunities throughout the post-purchase journey.

Define Hypotheses and Requirements: Translate insights into clear, testable hypotheses, establish success metrics, and create actionable product requirements that support effective execution.

Lead Cross-Functional Delivery: Collaborate closely with engineers, designers, analysts, and data and machine learning specialists to prioritize initiatives, coordinate timelines, and deliver product improvements efficiently.

Run Experiments and Measure Results: Plan and execute A/B tests and other product experiments, evaluate performance against defined metrics, and iterate on successful initiatives to maximize impact.

Drive Continuous Improvement: Take ownership of outcomes, adapt priorities based on evidence, and continuously refine the customer experience through a balance of data-driven decisions and practical problem-solving.

Requirements:

Product Management Experience: Proven experience in a B2C product role, with hands‐on responsibility for customer experience, customer journey design, activation, onboarding, or first-session optimization.

Discovery-Driven Product Expertise: Experience working with products that feature large volumes of offers, listings, or potential connections, where discovery and relevance are central to the customer experience.

Matching and Recommendation Systems: Familiarity with search relevance, recommendation engines, matching algorithms, content feeds, or similar systems designed to connect users with relevant options.

Segmentation and Personalization: Understanding of customer segmentation, personalization strategies, and data enrichment techniques to improve recommendation quality and user outcomes.

Relevant Industry Background: Experience in marketplaces, aggregators, dating or social discovery platforms, real estate, classifieds, large‐catalog e‐commerce, or other products built around discovery, matching, and recommendations.

Product Discovery and Hypothesis Development: Ability to identify customer problems, formulate testable hypotheses, define clear requirements, and translate insights into practical product solutions.

Experimentation and Analytical Skills: Experience designing and evaluating A/B tests and other experiments, interpreting product metrics, and using quantitative and qualitative research to valid