We’re hiring an analyst and builder for our Revenue Operations team to be a force multiplier for our go-to-market organization. Sometimes that means tackling a question with no playbook yet. Sometimes it means running an established process and improving it as you go.
You’ll take on ambiguous, high impact questions and turn them into clearly defined problems, design the right solution, and drive it through build, adoption, and continuous improvement.
The role has three modes. First, you’ll drive the analytical core: forecasting, executive reporting, revenue planning, QBR-grade analyses over large datasets, quota and target analytics, and the models that support forecasting and planning. You’ll present your own work directly to leadership and translate complex business questions into actionable insights.
Second, you’ll build net-new systems: internal tools, data models, and reporting infrastructure that teammates then run and scale. That includes planning models, dashboards, and operational workflows that make the business more efficient over time.
Third, you’ll make Revenue Operations more leveraged with AI, whether that’s building AI-assisted tooling, designing account scoring and research logic in our go-to-market stack, or automating work that shouldn’t be manual. You’ll constantly look for more opportunities to increase leverage across the organization.
The ideal candidate combines strong analytical horsepower with a systems mindset and genuine comfort with ambiguity. You ask why until you understand the business objective behind a request, you design solutions that scale beyond the first use case, and you already use AI to build and move faster than your job title suggests. You’re naturally curious about how AI can improve the way work gets done, but you know technology is only valuable when it solves a real business problem. And you finish: to you, work is done when it’s adopted, documented, and running without you, not when the analysis is shipped.
This role is based out of our NYC office.