高级增长产品经理（AI原生）
Senior Growth Product Manager AI Native
Magic Eden 在推出后仅用 9 个月就达到独角兽公司水平，是历史上最快的之一。我们从零开始打造了一个定义类别的 NFT 市场，并证明了我们懂得如何快速推进。现在我们再次这么做。Dicey 是我们的加密货币赌场和体育博彩平台，瞄准的是超过 1800 亿美元的 iGaming 和体育博彩市场。
我们是一个小型的完全远程团队。我们快速交付，亲自处理数据，并从零开始重新构建增长团队的运作方式，围绕 AI 进行重建。
职位描述
大多数 iGaming 行业依靠获取用户进行竞争。几乎没人能解决个性化留存问题，即了解玩家是谁、他们此刻需要什么，以及什么会真正改变他们本周的行为。这就是你将负责的问题。
这个职位专注于完整的注册后旅程：扩展我们的玩家分群框架，设计并执行针对性的优惠和活动，并负责由此带来的损益杠杆。它明确是 AI 原生的。你将构建工作流、代理和管道，运行生命周期活动，这些在过去需要一个团队两年时间才能完成。工作的一半是识别正确的问题，另一半是通过实验找到答案。
你会做什么
· 负责留存和变现作为增长循环。设定目标，寻找杠杆点，并推动所有玩家注册后发生的数据
- 负责玩家分群框架。目前是价值和风险。你决定它如何演进，哪些信号输入其中，以及公司其他部门如何使用它
- 构建 AI 原生的增长工具栈。分析、代理和自动化管道，能够提取分群、生成优惠候选，并以最少的人工操作运行活动
- 设计并发布针对特定分群和时刻的定向优惠：充值奖励、损失补偿、下注赏金、挑战、召回序列。确定它们的规模，制定规格，发布并测量效果
- 真实地在我们的数据仓库和链上数据中寻找模式，并在其他人之前将其转化为活动
- 扩展我们对玩家的信号：链上活动、状态匹配计划、社交账号链接，以及你能想到的其他任何内容
- 运行活动。邮件、应用内、Telegram，无论哪个渠道。你亲自参与，AI 完成大部分工作
- 与工程和设计团队合作，发布使这一切可重复的产品界面
- 我们寻找的人选
- 对玩家心理和激励设计有很强的直觉
查看英文原文
About Magic Eden and Dicey
Magic Eden reached unicorn status in just 9 months after launch, one of the fastest in history. We built a category-defining NFT marketplace from scratch and proved we know how to move fast. Now we're doing it again. Dicey is our crypto casino and sportsbook platform, targeting the $180B+ iGaming and sports betting markets.
We're a small, fully remote team. We ship fast, we're hands-on with our data, and we're rebuilding how a growth team operates around AI from the ground up.
The role
Most of the iGaming industry competes on acquisition. Almost nobody has figured out personalized retention, knowing who a player is, what they need right now, and what would actually change their behavior this week. That's the problem you'll own.
This role focuses on the full post-signup journey: expanding our player segmentation framework, designing and running targeted offers and campaigns, and owning the P&L lever that comes with it. It's explicitly AI-native. You'll build workflows, agents, and pipelines to run lifecycle campaigns that would have taken a whole team two years ago. Half the job is identifying the right problem. The other half is running the experiments to find the answer.
What you'll do
· Own retention and monetization as a growth loop. Set the targets, find the leverage, and drive the numbers for everything that happens after a player signs up
- Own the player segmentation framework. Today it's value and risk. You decide how it evolves, what signals feed it, and how the rest of the company uses it
- Build the AI-native growth stack. Analysis, agents, and automated pipelines that surface segments, generate offer candidates, and run campaigns with minimal manual work
- Design and ship targeted offers for specific segments and moments: reload bonuses, lossback, wager bounties, challenges, win-back sequences. Size them, spec them, ship them, measure them
- Spend real time in our data warehouse and on-chain data finding patterns and turn them into campaigns before anyone else does
- Expand the signals we have on players: on-chain activity, status-match programs, social account linking, and whatever else you can think of
- Run the campaigns. Email, in-app, Telegram, whatever the channel. You're hands-on with it, with AI doing the heavy lifting
- Partner with engineering and design to ship the product surfaces that make all of this repeatable
What we're looking for
· Strong intuition for player psychology and incentive design. Experience in gambling, gaming, fintech, or consumer marketplaces helps. Genuine curiosity about why people behave the way they do is required
- Deeply analytical. You can go from a vague question to a clean cohort cut yourself, without waiting on a data scientist
- AI-native by default. You already use AI to write queries, build analyses, and automate your own work and you want to push that much further
- High output with good judgment. You generate a lot of ideas and know which ones are worth testing first
- Bias to do it yourself. You're comfortable sending the email, running the query, and writing the spec, not just briefing others
- Comfortable with ambiguity. There's no playbook here, you'll be building it
Backgrounds that tend to fit
· Growth PM at a data-heavy consumer company
- MBB consultant who wants to move into product and own outcomes, not just advise on them
- Product Minded Data scientist or analyst who wants to ship, not just report
Why this is interesting
· Competitive, top-of-market compensation
- You're defining what a growth PM looks like in an AI-native company, there's no inherited playbook
- Personalised retention is where the industry is going and we're building it early
- Real ownership: a segmentation framework, a product surface, and a P&L lever, with a direct line to the founding team
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