Remote Product Owner — Recommendation Systems

Lever, Inc.; Turkey; On-site; TRY 5,879,000 - 8,819,000; Full time

Benefits offered by this job

Fully remote

Competitive compensation shared during

Vacation benefits

Wellness days

Training/ conference reimbursements

Health benefits

Home-office stipend

Recognition program

Global distributed team

Job summary

Lever, Inc. is seeking a Product Owner for a partner in Turkey to own the post-purchase experience, focusing on activation, matching, relevance, and personalized recommendations.

You will work across discovery, recommendation systems, segmentation, personalization, and experimentation, collaborating with engineering, design, analytics, and data/ML teams in a remote, international, fast-moving product environment.

Qualifications

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

Responsibilities

• Own post-purchase journey focusing on activation, matching and relevance.
• Optimize offer volume and recommendation quality for relevant selections.
• Improve relevance and trustworthiness of recommendations and invitations.
• Increase the likelihood of a quality match in the first week.
• Design and improve engagement mechanics like gamification and nudges.
• Collaborate with engineers, designers, analysts, and data/ML teams to deliver improvements.
• Run experiments (A/B tests) and analyze results to iterate.

Skills

Activation design

A/B testing

Cross-functional collaboration

Hypothesis-driven development

Data-driven decisions

Tools

A/B testing platforms

Job description

Lever, Inc. is seeking a Product Owner for a partner in Turkey to own the post-purchase experience, focusing on activation, matching, relevance, and personalized recommendations.

You will work across discovery, recommendation systems, segmentation, personalization, and experimentation, collaborating with engineering, design, analytics, and data/ML teams in a remote, international, fast-moving product environment.