The board
Harvey · Customer Experience- Pay
- $112,000–$168,000/yr
- Where
- Remote
- Posted
- Jun 15
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.
What you'd do
- 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
- 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
What they want
- 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