Revenue Operations Analyst

About Gusto

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff - payroll, health insurance, 401(k) s, and HR - so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

All full-time employees receive competitive base pay, benefits, and equity (RSUs) - because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy.

AI is a fundamental part of how work gets done  expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.

About the Role:

The Revenue Operations Analyst will help power Gusto Retirement's go‑to‑market engine with trustworthy data and decision‑ready insights. You will influence the strategy development & execution for the Retirement route to market. You'll spend most of your time building ad‑hoc analyses and dashboards that help Revenue leaders understand pipeline, performance, and opportunities to grow with equal focus on both our Sales and Marketing functions.

You'll use AI every day to standardize data, automate routine work, and prototype creative solutions that make our teams smarter and faster.

About the Team:

You'll join our Revenue Operations team supporting Gusto's revenue organization, with a focus on our Retirement Sales business. We help teams understand what's happening across the full revenue funnel-from marketing attribution and campaign performance to sales pipeline and conversion-and where to invest next. The team values clear thinking, tight execution, and a bias toward experimentation with AI to improve how we work.

You'll partner closely with the Revenue leadership team and fellow operators to turn questions into structured analyses and actionable recommendations.

Here's what you'll do day-to-day:

* Own fast, accurate ad‑hoc reporting and analysis to answer questions from Revenue leadership and cross‑functional partners (e.g., pipeline, conversion, marketing attribution, campaign performance, productivity, and forecasting).

* Use AI tools to clean, enrich, and standardize data (e.g., de‑duping, categorization, text cleanup, field mapping) and to document assumptions and workflows.

* Build and maintain revenue dashboards and standardized reporting that provide self‑serve visibility into performance and funnel health.

* Support Marketing with reporting on lead generation, campaign ROI, channel attribution, and funnel contribution, partnering closely with marketing stakeholders to define metrics and build self-serve visibility.

* Partner with Sales, Marketing, and Product to design creative solutions-from lightweight prototypes to repeatable workflows and automations.

* Translate ambiguous business questions into structured problem statements, clear metrics, and analysis plans, then summarize findings into decision‑ready narratives.

* Proactively monitor data quality, investigate anomalies, and propose fixes that keep our reporting accurate, consistent, and trustworthy.

* Contribute to and maintain documentation for data definitions, metric logic, and reporting standards, so stakeholders have a single source of truth.

Here's what we're looking for:

* 2-5 years of experience in revenue analytics, business/revenue operations, product operations, or a similar analytical role, ideally in a SaaS or sales‑driven environment.

* Hands‑on experience querying and transforming data using SQL and spreadsheets (Google Sheets/Excel), and building dashboards or reports in BI tools (e.g., Tableau, Looker, Mode, or Salesforce reports).

* Familiarity with CRM and GTM systems (e.g., Salesforce, sales engagement or marketing automation tools) and comfort turning business questions into analysis requirements.

* Demonstrated AI fluency: you regularly use AI tools to clean data, structure datasets, generate code or formulas,…