Product Owner (Matchmaking) İş İlanı

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 Turkey. 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 validate decisions. Product Delivery and Prioritization: Demonstrated ability to manage product requirements, prioritize initiatives, coordinate delivery, and drive projects from discovery through implementation and evaluation. Cross-Functional Collaboration: Strong communication and collaboration skills, with the ability to work effectively with designers, engineers, analysts, and data specialists. Results-Oriented Mindset: Focus on measurable business and customer outcomes rather than process for its own sake, with a proactive approach to identifying and pursuing growth opportunities. Ownership and Adaptability: Comfortable taking responsibility without waiting for direction, navigating changing priorities, and making decisions in a dynamic environment. Clear Communication and Resilience: Able to communicate ideas directly and effectively, learn from unsuccessful experiments, and use setbacks as opportunities for continuous improvement. Benefits Fully Remote Work: A full-time remote opportunity offering flexibility to work from different locations. Competitive Compensation: Salary details and the initial pay range will be shared with candidates during the recruitment process and before employment begins. Annual Vacation: 28 calendar days of paid vacation per year. Wellness Days: Seven additional wellness days annually to manage personal responsibilities, rest, and recharge without using sick leave. Referral Bonuses: Bonuses of up to $5,000 for recommending successful candidates for available positions. Professional Development: 50% reimbursement for eligible professional training, international conferences, and industry events. Language Learning: Corporate discounts on English lessons. Health Benefits: Depending on eligibility for corporate medical insurance, reimbursement of up to $1,000 gross per year for eligible employees to help cover personal health insurance or medical expenses for themselves and close relatives, including spouses and children. Home Office Support: Access to equipped office or coworking spaces where available, or reimbursement of up to $1,000 gross every three years toward eligible home office equipment, internet, or coworking expenses. Peer Recognition and Rewards: An internal gamified appreciation system that allows employees to earn bonuses from colleagues and exchange them for company merchandise, team-building activities, massage certificates, and other rewards. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.