Revenue Operations Analyst

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, summarize insights, or prototype new reporting/automation workflows, and you’re eager to stay current on emerging AI capabilities.
• Strong analytical and problem‑solving skills with a high bar for data quality, attention to detail, and the ability to prioritize among competing requests.
• Clear, concise communication skills—you can turn complex analysis into simple stories, recommendations, and visuals for non‑technical stakeholders.
• Bachelor’s degree in a quantitative, business, or related field (e.g., economics, statistics, business, engineering) or equivalent practical experience.

Our cash compensation amount for this role is targeted at $107,235 - $126,000 in San Francisco and New York, and $88,510 - $104,000 in Denver and most remote locations. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.