客户体验分析师
CX Data Analyst
为什么选择Harvey
在Harvey，我们正在改变法律和专业服务的运作方式。通过结合前沿的代理AI、企业级平台和深厚的行业专业知识，我们正在重塑未来数十年关键知识工作的完成方式。
这是一个难得的机会，帮助打造一家具有代际影响力的公司，在真正的转折点上共同成长。我们拥有强大的产品市场匹配度和世界级的投资支持。我们正在快速扩展，并实时定义一个新类别。这项工作充满雄心，标准很高，个人、职业和财务上的成长机会无与伦比。
我们的团队行动迅速，有责任感，并对使命充满热情——以高强度运作，贴近客户，不断追求卓越。我们秉持三个价值观：果断、简洁、工作未完成。我们在明确判断下快速行动，而非等待完美信息；我们相信简洁才是可扩展的关键；我们从不满足于现状。如果你希望与志同道合的人一起完成职业生涯中最出色的工作，我们期待与你携手共创。
在Harvey，专业服务的未来正在今天被书写——而我们才刚刚开始。
职位概述
客户体验依赖数据——但目前，这些数据分散在太多地方，使用太多语言，且传递给错误的人太晚。这个职位的存在就是为了解决这个问题。
作为Harvey的首位支持运营数据分析师，你将负责客户体验部门的分析职能。你将构建并维护仪表盘、报告和反馈机制，帮助我们判断是否达到了我们的北极星指标——净推荐值（cSAT）、首次响应时间（TTR）、质量评估（QA）评分、升级率等，并在数字背后发现信号，以便采取行动。你将隶属于支持运营团队，向支持运营经理汇报，并与客户体验领导层和Harvey的中央数据团队紧密合作，确保随着业务扩展，该部门具备正确的工具和指标。
这是一个独立岗位。你不会下面有团队。你需要足够精通支持分析，能够独立承担该职能，有足够的自信去质疑指标的呈现方式，并且足够高效，能够跟上Harvey的节奏。
你将负责
- 负责客户体验的定期报告——每周、每月以及季度回顾（QBR）准备，针对运营、管理层和跨职能受众进行定制
- 将支持数据转化为清晰的叙述：发生了什么，原因是什么，
查看英文原文
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
Customer Experience runs on data — but right now, that data lives in too many places, speaks too many languages, and reaches the wrong people too late. This role exists to fix that.
As Harvey's first Support Operations Data Analyst, you'll own the analytics function for the Customer Experience org. You'll build and maintain the dashboards, reports, and feedback loops that tell us whether we're hitting our north stars — cSAT, TTR, QA scores, escalation rates — and surface the signal underneath the numbers so we can act on it. You'll sit within the Support Operations team, reporting to the Support Operations Manager, and work closely with Customer Experience leadership and Harvey's central data team to ensure the org is equipped with the right instrumentation as we scale.
This is a solo role. You won't have a team beneath you. You will need to be fluent enough in support analytics to hold the function independently, confident enough to push back on how metrics are framed, and fast enough to operate at Harvey's pace.
WHAT YOU'LL DO
- Own recurring reporting for Customer Experience — weekly, monthly, and QBR-ready — tailored to ops, leadership, and cross-functional audiences
- Translate support data into clear narratives: what's happening, why, and what to do about it
- Track and maintain north star metrics: cSAT, TTR by tier, QA scores, bug escalation rate to EPD, and First Response Time
- Build and maintain self-serve dashboards that give the ops team and leadership real-time visibility into support performance
- Partner with Support Systems to ensure Zendesk is instrumented to capture the data we need
- Work with Harvey's central data team to connect support data to broader product and customer data sources
- Identify and close data collection gaps — if we can't measure it, help define how we should
- Design feedback loops that connect support signals to Product, Engineering, and Customer Success
- Quantify the operational cost of product bugs, feature gaps, and onboarding failures
- Contribute to QA analytics as the QA program matures
- Track ticket deflection, AI/chatbot performance, and self-service effectiveness
- Measure the impact of AI-driven support — containment rate, escalation rate from AI interactions, resolution quality — and surface findings that drive how we tune and invest in those tools
- Support ad hoc analytical requests from the Support Operations Manager, Customer Experience leadership, and senior stakeholders
WHAT YOU HAVE
Required
- 3–5 years of experience in analytics, with at least 2 years directly in support operations, customer success operations, or a closely adjacent function
- Fluency in support platform data — you know how Zendesk (or equivalent) is structured, what data it produces, and what it doesn't
- SQL proficiency — you can write complex queries against large datasets without hand-holding (CTEs, window functions, joins across schemas)
- Dashboard experience — you've built and maintained operational dashboards in Looker, Tableau, Sigma, Omni, or equivalent
- Reporting for multiple audiences — you know the difference between what a frontline manager needs and what a CFO needs, and you build accordingly
- Strong data storytelling — you don't just present numbers, you write the narrative
- Comfort operating solo — you don't need a team around you to deliver, and you don't need a ticket to tell you what to look at
Strong Plus
- Experience with Python for data manipulation or automation
- Familiarity with dbt or similar data transformation tooling
- Experience building or contributing to QA analytics programs
- Background supporting enterprise SaaS or AI-native products
- Experience working with Zendesk APIs or extracting data beyond standard reporting
Key Attributes
- AI-native: you use AI tooling actively in your analytical workflows — not as a novelty, but as a force multiplier
- Pace: you move in hours and days, not weeks. You surface findings before anyone has to ask
- Judgment: you know which metrics matter and which are vanity. You push back when framing is wrong
- Clarity: your outputs are direct, jargon-free, and actionable. You write for the reader, not yourself
- Ownership: you treat Customer Experience analytics as your problem to solve, not a ticket queue to process
COMPENSATION
$112,000 - $168,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922].
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Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai