数据分析师，用户运营
Data Analyst, User Operations
我们的使命是自动化编码。我们旅程的第一步是通过创新研究、设计和工程的结合，打造最棒的专业程序员工具。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。
关于职位
用户运营团队负责Cursor用户的体验——从个人开发者到我们最大的企业客户。随着我们在各个地区的扩展，支持数据的数量和丰富性增长速度超过了我们理解它的能力。我们正在寻找一名数据分析师来改变这一现状。
该职位位于产品与工程部门，向用户运营主管汇报，负责支持的数据和报告层。你将把工单数据、SLA表现、客户情绪和产品信号转化为领导用来管理组织的仪表盘和分析结果，以及产品和工程团队用来决定下一步修复什么的依据。支持是反映产品是否有效运行的最清晰信号之一。你的工作就是让这个信号变得可读。
你将负责的工作
- 构建并维护支持的报告层：工单数量、SLA达成率、解决时间、帮助中心表现、CSAT/CES/情绪、以及各地区和层级的利用率
- 与支持领导合作，将开放性问题——“我们是否变得更快速但准确性下降了？”、“企业客户的痛点集中在哪些地方？”——转化为推动决策的分析
- 维护多信号模型用于错误和问题的优先级排序，考虑频率、广度、支持成本和情绪等因素，使工程团队看到一个有说服力的用户影响图景
- 为两个受众设计仪表盘：面向管理人员的内部操作视图，以及面向企业客户的客户视图
- 负责支持数据产品中的数据质量、治理和可靠性，包括我们的工单数据和内部承诺
- 将客户之声的趋势呈现给产品、工程和市场拓展团队，并帮助在用户反馈与实际开发之间形成闭环
你可能适合这个职位，如果你
- 有5年以上数据分析师、分析工程师或类似岗位的经验
- 具备扎实的SQL技能——这是你的主要工具——并且你能够熟练构建数据管道和模型
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.
About the role
The User Operations team owns the support experience for Cursor's users - from individual developers to our largest enterprise accounts. As we've scaled across regions, the volume and richness of our support data has grown faster than our ability to make sense of it. We're looking for a Data Analyst to change that.
This role sits inside our Product and Engineering organization with a dotted line to the Head of User Operations and owns the data and reporting layer for Support. You'll turn ticket data, SLA performance, customer sentiment, and product signal into the dashboards and analysis that leadership uses to run the org - and into the evidence Product and Engineering use to decide what to fix next. Support is one of the clearest signals we have about where the product is working and where it isn't. Your job is to make that signal legible.
What you'll do
- Build and own the reporting layer for Support: ticket volume, SLA attainment, resolution times, help center performance, CSAT/CES/sentiment, and capacity utilization across regions and tiers
- Partner with Support leadership to turn open questions - "are we getting faster but less accurate?", "where is enterprise pain actually concentrated?" - into analysis that drives decisions
- Maintain the multi-signal model behind bug and issue prioritization, weighting frequency, breadth, support cost, and sentiment, so Engineering sees a defensible picture of what impacts users most
- Design dashboards for two audiences: internal operational views for managers, and customer-facing views for enterprise accounts
- Own data quality, governance, and reliability across Support data products, including our ticketing data and internal commitments
- Surface Voice of Customer trends to Product, Engineering, and GTM, and help close the loop between what users report and what actually gets built
You may be a fit if
- You have 5+ years of experience in data analytics, analytics engineering, or a similar role
- You have strong SQL skills - this is your primary toolkit - and you're comfortable building models and transformations (dbt or equivalent)
- You've built reporting and dashboards in production that people actually depend on, not one-off charts
- You can take a vague operational question and turn it into the right analysis without a playbook
- You communicate clearly with both technical and non-technical stakeholders, and you're honest about what the data does and doesn't support
- You're self-directed and comfortable owning ambiguous problems end to end