AI-Native Growth PM: Retention & Segmentation Lead in Perth

AI-Native Growth PM: Retention & Segmentation Lead in Perth

Perth Full-Time 56250 - 68750 $ / year (est.) On-site
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At a Glance

  • Tasks: Lead post-signup lifecycle, design targeted offers, and drive AI-native campaigns.
  • Company: Join Magic Eden, a leader in innovative growth strategies.
  • Benefits: Competitive salary, flexible work hours, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on innovation and collaboration.
  • Why this job: Make an impact by optimising retention and monetisation with cutting-edge AI technology.
  • Qualifications: Experience in product management and a passion for data-driven growth.

The predicted salary is between 56250 - 68750 $ per year.

Magic Eden is seeking a Growth Product Manager to own the post-signup lifecycle, expanding segmentation, designing targeted offers, and driving AI-native campaigns across channels.

You will build workflows, agents, and pipelines to run lifecycle programs.

You will collaborate with engineering and design to ship repeatable growth surfaces, using on-chain data and rapid experimentation to optimize retention and monetization.

AI-Native Growth PM: Retention & Segmentation Lead in Perth employer: Zim Directory

At Magic Eden, we pride ourselves on being a fast-paced, innovative employer that empowers our remote team to redefine the iGaming landscape. As a Senior Growth Product Manager AI Native, you'll enjoy competitive compensation, real ownership of your projects, and the opportunity to shape the future of personalized retention in a dynamic environment. Our culture fosters creativity and collaboration, ensuring you have the resources and support needed for professional growth while working on cutting-edge AI-driven solutions.

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Contact Details:

Zim Directory Recruitment Team

We think you need these skills to ace AI-Native Growth PM: Retention & Segmentation Lead in Perth

Growth Product Management
Segmentation
AI-Native Campaigns
Workflow Design
Data Analysis
Collaboration with Engineering
Collaboration with Design