--- title: 'CX Data Analyst at Harvey' canonical: 'https://feeny.ai/job/cx-data-analyst-harvey-san-francisco-be3kpm5dfvbb' type: 'job' last_seen: '2026-09-07' --- # CX Data Analyst at Harvey - **Company:** [Harvey](https://feeny.ai/companies/harvey) - **Location:** San Francisco, CA - **Compensation:** $112k–$168k - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-06-15 - **Last confirmed live:** 2026-09-07 - **Apply:** https://jobs.ashbyhq.com/harvey/ecfc45be-fc15-4c16-a419-509c998b6c80/application **Skills:** SQL, Zendesk, Looker, Tableau, Sigma, Omni, Data storytelling, Dashboard building, Python, dbt, Zendesk APIs > Own the analytics function for User Operations, building dashboards and reports to track support performance metrics like cSAT and TTR. Partner with central data and product teams to improve instrumentation and drive operational improvements. ## Job description ## 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]. ## #LI-ML1 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 ## About Harvey ## Company Overview - **One-liner**: Harvey builds domain-specific AI software for legal and professional services, enabling law firms and in-house teams to automate research, contract analysis, due diligence, and complex workflows. - **Entity Type**: Private (backed by leading venture capital firms) - **Headquarters**: San Francisco, California, United States - **Founded**: 2022 - **Founders**: Winston Weinberg (CEO), Gabriel Pereyra (President) ## Core Business - **Primary industry**: AI software for legal and professional services (LegalTech) - **Target customers**: B2B – large law firms (AmLaw 100), in-house legal teams at Fortune 500 enterprises, mid-sized firms, and professional service networks across 60+ countries. - **Mission or purpose statement**: To enable legal and professional services teams to focus on high-value work by providing a secure, expert AI platform that handles research, drafting, and complex workflows. ## Products & Services - **Harvey Assistant**: Ask questions, analyze documents, and draft faster with domain-specific AI (SaaS). - **Harvey Vault**: Securely store, organize, and bulk-analyze legal documents (SaaS). - **Harvey Knowledge**: Research complex legal, regulatory, and tax questions across domains (SaaS). - **Harvey Agents**: Purpose-built agents that execute complex legal work end-to-end (SaaS). - **Harvey Contract Intelligence**: Surface insights, strengthen negotiations, and accelerate reviews (SaaS). - **Harvey Command Center**: Analytics, benchmarking, and agentic insights for leading AI transformation (SaaS). - **Harvey Mobile**: Mobile access to stay productive from anywhere (SaaS). - **Harvey Shared Spaces**: Collaborate with legal teams across organizations in secure shared workspaces (SaaS). - **Harvey Ecosystem**: Integration with existing tools to ground answers in trusted sources (API/platform). ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed (company is private). - **Key Metric**: Annual Recurring Revenue (ARR) – reported in press but exact figure not disclosed; strong growth implied by 1,500+ customers and rapid hiring. - **Notable Investors/Partners**: Sequoia, Kleiner Perkins, GV (Google Ventures), OpenAI Startup Fund, Coatue, Andreessen Horowitz, EQT. - **Growth Signals**: - Named Time100 Most Influential Companies (2025). - LinkedIn Top 50 Startup of 2025. - CNBC Disruptor 50 List. - 1,500+ customers across 60+ countries, including AmLaw 100 firms. - Headcount: ~300 employees (as of mid-2025), with aggressive hiring (254 active job postings). - Office expansion: San Francisco, New York City, London. ## Competitive Advantages - **Domain specialization**: AI models trained specifically for legal and professional services, not generic LLMs. - **Enterprise security**: SOC 2 Type II, ISO 27001/27701/42001, GDPR, CCPA compliance – meeting law firm security requirements. - **Deep investor backing**: World-class VC network provides strategic guidance and access. - **Strong product‑market fit**: Rapid adoption by top-tier law firms and in-house teams, with high switching costs due to embedded workflows. - **First‑mover in agentic legal AI**: Purpose‑built agents execute end‑to‑end tasks, differentiating from simple document Q&A tools. ## Strategic Focus - **Customization, collaboration, and simplicity**: Helping teams embed expertise into Harvey, collaborate across firms, and reduce complexity via agentic workflows. - **Expansion beyond legal**: Long‑term ambition to transform professional services broadly (consulting, accounting, etc.). - **Product innovation**: Continued investment in agentic AI, mobile access, and ecosystem integrations. - **Global growth**: Scaling sales and engineering teams in existing hubs and expanding into new markets. ## Why Work Here - **Culture**: Fast‑paced, collaborative, ambitious. Values include **Decisiveness** (“take the square root of the weather” – avoid overanalysis), **Simplicity**, and **Job’s Not Finished** (continuous improvement). - **Work environment**: Hybrid – 3+ days per week in office for roles based in San Francisco, New York City, or London. Some fully remote positions available (clearly marked). - **Benefits**: Comprehensive health/dental/vision insurance, 401(k) match, paid parental leave (immediately eligible), annual professional development stipend, in‑office daily lunch, and more. - **Growth opportunities**: Rapidly scaling (~300 employees, 254 open roles) provides internal mobility and ownership of impactful projects. - **Engineering culture**: Strong blend of AI research (DeepMind background) and legal domain expertise. CTO Siva Gurumurthy recently joined. Emphasis on building secure, enterprise‑grade products. ## Sources 1. [harvey.ai](https://www.harvey.ai/) 2. [harvey.ai/company](https://www.harvey.ai/company) 3. [harvey.ai/blog/landing-a-job-at-harvey](https://www.harvey.ai/blog/landing-a-job-at-harvey) 4. [linkedin.com/company/harvey-ai](https://www.linkedin.com/company/harvey-ai) 5. [jobs.ashbyhq.com/harvey](https://jobs.ashbyhq.com/harvey) ## Other roles at Harvey - [Staff Software Engineer, Model Infrastructure](https://feeny.ai/job/staff-software-engineer-model-infrastructure-harvey-san-francisco-8a16y83nftsj) — San Francisco, CA - [Senior Software Engineer, Model Infrastructure](https://feeny.ai/job/senior-software-engineer-model-infrastructure-harvey-san-francisco-6tywmebr0r9h) — San Francisco, CA - [Head of Mid-Market Sales](https://feeny.ai/job/head-of-mid-market-sales-harvey-london-n918xg1r4jgb) — London, United Kingdom - [Customer Experience Manager, US](https://feeny.ai/job/customer-experience-manager-us-harvey-san-francisco-2dw5w8905rz6) — San Francisco, CA - [Transformation Associate](https://feeny.ai/job/transformation-associate-harvey-san-francisco-qm17099y4cjc) — San Francisco, CA - [Transformation Associate](https://feeny.ai/job/transformation-associate-harvey-chicago-h0b3a2pdz2zp) — Chicago, IL - [Transformation Associate](https://feeny.ai/job/transformation-associate-harvey-dallas-a2hzwnh0vb51) — Dallas, TX - [Transformation Associate](https://feeny.ai/job/transformation-associate-harvey-remote-cezdb49eyhv5) - [Transformation Associate](https://feeny.ai/job/transformation-associate-harvey-new-york-78kzq8sv2gvp) — New York, NY - [Content Marketing Manager](https://feeny.ai/job/content-marketing-manager-harvey-san-francisco-zsjew4mcankn) — San Francisco, CA