Magic Eden

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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