Revenue Operations Analyst

This role is focused on Jeeves’s growth programs and emerging revenue channels , including our partnerships channel and new market expansion initiatives , where we need rigorous, scalable analytics to match the pace of growth.

You’ll be responsible for the analytical layer that connects our sales activity to revenue outcomes: building the dashboards our leadership relies on, maintaining shared responsibility for the integrity of our performance data, and proactively surfacing the insights that shape how we operate.

Key Responsibilities:

GTM Analytics & Growth Program Insights

• Build and maintain Tableau dashboards tracking performance across our partnerships channel and new growth initiatives , serving audiences from country leads to executive leadership.
• Analyze conversion rates, pipeline health, ramp trends, and revenue attainment across programs and segments, surfacing patterns before they become decisions that have already been made.
• Come with a point of view. When a program is underperforming or a trend shifts, bring an interpretation and a recommendation (not just a chart).

Revenue Planning & Target Analysis

• Contribute to GTM capacity planning and quota-setting cycles , modeling scenarios, building attainment reports, and stress-testing assumptions before plans are finalized.
• Maintain performance-against-target reporting for growth programs and emerging channels: track attainment, flag outliers early, and ensure data is always reconciled.
• Support variable compensation analysis for relevant programs , running calculations, auditing for accuracy, and partnering with Finance to ensure payouts are correct and timely.

AI-Driven Operations & Scale

• Use AI tools, including Claude and other frontier models, as active parts of your workflow: automating repetitive reporting tasks, accelerating data synthesis, and building scalable analytical programs that would otherwise require a much larger team.
• Identify RevOps processes that can be operationalized or significantly improved through AI, and take ownership of building those solutions, not just flagging the opportunity.
• Apply AI-assisted analysis to extract insights at scale from large, multi-source datasets: pipeline signals, rep activity, customer behavior, and market trends.

Data Quality & Systems Integration

• Share responsibility for data quality across our revenue stack (HubSpot CRM, Tableau, and financial systems), conducting audits for accuracy, completeness, and consistency.
• Connect disparate data sources (CRM, marketing automation, financial tools, and proprietary revenue data) so that reporting on growth programs is unified and trustworthy.
• Document data models, metric definitions, and reporting logic so the team works from a shared understanding of what we’re measuring and why.

Stakeholder Partnership

• Develop enough context on our GTM motion to contribute meaningfully in planning and pipeline review cycles alongside sales leadership, bringing data that drives decisions, not just awareness.
• Serve as a reliable analytical resource to the Head of Revenue Operations and GTM leadership: scope requests clearly, pull the data, and return clear answers quickly.
• Identify process gaps and proactively propose improvements to how we collect, manage, and act on GTM data (especially across new and growing channels).

What We’re Looking For

Technical & Analytical Skills

• Tableau mastery: able to write complex calculated fields, build multi-source dashboards, and design views for diverse audiences from reps to the C-suite.
• Advanced Excel and Google Sheets: complex formulas, pivot tables, and financial modeling , you reach for the right tool for the job, not just the most impressive one.
• Strong SQL skills: you can get to an answer independently without waiting for a data engineer to pull it for you.
• Data integration experience: comfortable connecting CRM, marketing automation, and financial data into unified reporting environments.
• Business metrics fluency: deep understanding of conversion rates, customer lifetime value (LTV), pipeline coverage, ramp curves, revenue attainment, and customer health.
• Data modeling: able to design clean structures that support accurate forecasting, compensation analysis, and multi-region rollups.

AI Fluency (Required, Not Optional)

• You actively use AI tools, Claude Copilot/Code, or equivalent, as part of your day-to-day workflow, not as a novelty.
• You’ve used AI to automate reporting pipelines, accelerate analysis, or build operational programs that scale beyond what a single analyst could.