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Support Operations Data Analyst
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Harvey·San Francisco·15 июня

Support Operations Data Analyst

🏢 ОфисMiddleПолная занятость
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Наша компания

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.

О роли

This is a rare chance to help build a generational company at a true inflection point. With 1500+ customers in 60+ countries, 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, take

Чем предстоит заниматься

Own recurring reporting for User Operations — 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, User Operations leadership, and senior stakeholders
WHAT YOU HAVE

Наши требования

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
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

Дополнительно

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 User Operations analytics as your problem to solve, not a ticket queue to process
$112,000 - $168,000 USD
H
Harvey
San Francisco

ГрейдMiddle
ЗанятостьПолная занятость
РегионСША
ФорматОфис
ИсточникСкрыто
Опубликовано15 июня
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