Support Operations Data Analyst

What You'll Do 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 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 User Operations 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 ]. #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 [email protected]

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