全栈分析师，GTM
Full Stack Analyst, GTM
我们致力于自动化编码。我们旅程的第一步是打造最好的工具，供专业程序员使用，结合创新研究、设计和工程。我们的组织结构非常扁平，团队小而人才密集。我们特别喜欢那些追求真理、充满热情且富有创造力的人。我们享受激烈的辩论、疯狂的想法以及发布代码。
SpaceXAI正在快速进入企业AI编码市场，我们的GTM组织也在迅速扩展。作为GTM分析团队的首批员工之一，你将是团队中最资深的个人贡献者——既要构建GTM运行的数据基础设施，又要将其转化为领导层用来做决策的指标、模型和洞察。
职位简介
这是一个亲力亲为、影响深远的职位。你将为团队设定技术和分析的标准。你将负责对团队至关重要的GTM数据模型和流程，构建一个值得信赖的语义层，销售代表和领导层可以在此基础上进行开发，并利用这一基础回答关于推动销售渠道、转化率和留存率的难题。你将定义GTM以AI优先的方式与数据互动，与GTM应用团队和RevOps合作，保持工具的一致性，并与产品数据和企业工程团队合作，获取所需数据。
你将负责
- 负责驱动分析的GTM数据模型和流程——构建和维护它们，设定高质量标准，并创建一个安全且一致的语义层，GTM可以在此基础上进行开发。
- 对收入增长（及阻碍）因素进行深入分析：漏斗转化、细分表现、客户成功和销售代表生产力。
- 优化领导层计划的预测、配额和产能模型，并对这些模型背后的假设进行压力测试。
- 定义GTM以AI优先的方式与数据互动——哪些内容通过Cursor自助完成，哪些内容预先构建到受控仪表盘和应用程序中。
- 与产品数据和企业工程团队合作，确保GTM获得所需数据，并尽可能使用一致的流程、定义和模型。
你可能适合这个职位，如果
- 你的SQL能力非常出色（不可妥协），并且你能够熟练处理大型复杂数据集。
- 你构建并维护过生产环境的数据流程和模型，并能快速掌握不熟悉的数据库结构——包括CRM和GTM系统。
- 你构建过预测、配额或产能模型，并且是一个强大的模型构建者。
查看英文原文
Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.
SpaceXAI is expanding rapidly into the Enterprise AI coding market, and our GTM organization is scaling just as fast. As one of the first hires on our GTM Analytics team, you'll be the most senior IC on the team — both building the data infrastructure GTM runs on and turning it into the metrics, models, and insights leadership uses to make decisions.
About the role
This is a hands-on, high-leverage role. You'll set the technical and analytical bar for the team. You'll own the GTM data models and pipelines that matter, build a trustworthy semantic layer reps and leadership can build from, and use that foundation to answer the hard questions about what's driving pipeline, conversion, and retention. You'll define how GTM interacts with data in an AI-first way, work with the GTM Apps team and RevOps to keep tooling consistent, and partner with the product Data and Enterprise Engineering teams to get the data you need.
What you’ll do
- Own the GTM data models and pipelines that power analysis - building and maintaining them, setting high quality standards, and creating a safe and consistent semantic layer GTM can build on.
- Run deep-dive analyses on what's driving (and blocking) revenue: funnel conversion, segment performance, customer success, and rep productivity.
- Optimize the forecasting, quota, and capacity models leadership plans against, and pressure-test the assumptions behind them.
- Define how GTM interacts with data in an AI-first way—what's self-serve via Cursor and what's prebuilt into governed dashboards and applications.
- Partner with the product Data and Enterprise Engineering teams to ensure GTM has the data it needs and uses consistent pipelines, definitions, and models wherever possible.
You may be a fit if
- Your SQL is exceptional (non-negotiable), and you're fluent working across large, complex datasets.
- You've built and maintained production data pipelines and models, and you pick up unfamiliar data structures quickly—CRM and GTM systems included.
- You've built forecasting, quota, or capacity models, and you're a strong modeler in both code and spreadsheets.
- You can operationalize metrics and tooling for non-technical stakeholders so they can self-serve.
- You have strong analytical judgment and can move between the big picture and the details—from "how should we measure GTM health?" to "why is this one segment's conversion off?"
- Direct experience with GTM, revenue, or sales analytics is preferred, but a strong analytics or data-science background and the drive to go deep on the GTM domain matter more.
- You operate with high ownership, are comfortable pushing back on senior leaders, and bias toward durable systems over one-off decks.