Remote Product Owner: Recommendation Systems

Lever, Inc.; Ireland; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Health benefits

Vacation days (28) and wellness days

Remote-first environment

Professional development reimburse

Job summary

Lever, Inc. is seeking a Product Owner for Recommendation Systems based in Ireland. You will own the post-purchase customer experience, focusing on activation, matching, relevance, and personalized recommendations, collaborating with engineering, analytics, and ML teams.

You will translate hypotheses into testable experiments, drive delivery from idea to impact, and own measurable outcomes in a remote, international environment.

Qualifications

• Hands-on B2C product experience, focusing on activation, onboarding and first-session experiences.
• Experience with discovery-driven products with large volumes of offers or matches.
• Understanding of search, feed relevance, matching, personalization or related product experiences.
• Experience with segmentation, personalization and enriching offers/listings with data.
• Experience in marketplaces, aggregators, or discovery/recommendation driven products.

Responsibilities

• Own the post-purchase customer journey, focusing on activation, matching, relevance, and value realization.
• Optimize offer volume and recommendation quality to deliver a relevant, but not overwhelming, selection.
• Improve relevance and trustworthiness of recommendations; increase relevant invitations reaching paying customers.
• Design engagement mechanics like gamification, nudges, reminders, and reactivation features.
• Run A/B tests, analyze results, and iterate or scale solutions based on evidence.

Skills

B2C product experience

customer journey design

activation/onboarding

A/B testing

data-informed decision making

cross-functional collaboration

Job description

Lever, Inc. is seeking a Product Owner for Recommendation Systems based in Ireland. You will own the post-purchase customer experience, focusing on activation, matching, relevance, and personalized recommendations, collaborating with engineering, analytics, and ML teams.

You will translate hypotheses into testable experiments, drive delivery from idea to impact, and own measurable outcomes in a remote, international environment.