About Magic Eden and Dicey
Magic Eden reached unicorn status in just 9 months after launch, one of the fastest in history. They built a category-defining NFT marketplace from scratch and are now developing Dicey, a crypto casino and sportsbook platform targeting the $180B+ iGaming and sports betting markets. The team is small and fully remote, focusing on fast shipping, data-driven decisions, and rebuilding growth operations around AI.
The role
The position focuses on personalized retention in the iGaming industry, owning the full post-signup journey. Responsibilities include expanding the player segmentation framework, designing and running targeted offers and campaigns, and managing the associated P&L lever. The role is explicitly AI-native, involving building workflows, agents, and pipelines to run lifecycle campaigns efficiently. Half the job is problem identification, the other half is running experiments to find solutions.
What you'll do
— Own retention and monetization as a growth loop, setting targets, finding leverage, and driving post-signup metrics
— Own and evolve the player segmentation framework, deciding signals and company usage
— Build the AI-native growth stack including analysis, agents, and automated pipelines for segment surfacing, offer generation, and campaign execution
— Design and ship targeted offers such as reload bonuses, lossback, wager bounties, challenges, and win-back sequences; size, specify, ship, and measure them
— Analyze data warehouse and on-chain data to find patterns and create campaigns proactively
— Expand player signals including on-chain activity, status-match programs, social account linking, and others
— Run campaigns across channels like email, in-app, Telegram, with AI handling heavy lifting
— Collaborate with engineering and design to create product surfaces that enable repeatable processes
What they're looking for
— Strong intuition for player psychology and incentive design; experience in gambling, gaming, fintech, or consumer marketplaces is helpful
— Deep analytical skills, able to independently perform cohort analyses without waiting for data scientists
— AI-native mindset, already using AI to write queries, build analyses, and automate work, with desire to advance further
— High output with good judgment, generating many ideas and prioritizing tests effectively
— Bias to do it yourself, comfortable executing emails, queries, and specs personally
— Comfortable with ambiguity and building new playbooks
Backgrounds that tend to fit
— Growth PM at data-heavy consumer companies
— MBB consultants transitioning to product ownership
— Product-minded data scientists or analysts focused on shipping rather than reporting
Why this is interesting
— Competitive, top-of-market compensation
— Defining the role of a growth PM in an AI-native company without existing playbooks
— Early involvement in personalized retention, a key industry trend
— Real ownership of segmentation framework, product surface, and P&L lever with direct access to founders
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