Strategic advisor and operating partner to the VP of Global Customer Success. Own customer retention, expansion, and post-sales operations by building data systems, forecasting, and AI tooling at a B2B SaaS company.
183k – 248k/yr
Hybrid5+ YOERevenue Operations
About the role
Responsibilities
Customer analysis at the account level. Get hands-on with the data to understand what drives expansion, what predicts churn, and where the highest-leverage interventions live. Connect product usage signals, customer health, and commercial outcomes and translate the findings into decisions the CS org acts on.
Forecasting and pipeline rigor for the post-sales motion. Build and evolve how we forecast GRR, NRR, and expansion pipeline. Wire up the inputs yourself.
The CS operating cadence. Run the rhythm - business reviews, executive deep dives, leadership offsites - and make sure the right questions get asked with the right data behind them.
CS systems and tooling. Partner with our systems team on our CS platform and its integrations with Salesforce and our product data.
AI as a force multiplier. Build skills, agents, and automations that the whole CS org can adopt.
Strategic partnership with Global CS leadership. Act as a true business partner in the room, in the work, jointly owning the outcomes. Coordinate with peers supporting other functions to make sure the post-sales view connects to the broader GTM picture.
Requirements
5+ years operating in Revenue Strategy, Sales Strategy, CS Operations, or Business Operations at a high-growth B2B SaaS company. Ideally smaller, fast-moving environments where you own outcomes end-to-end.
Direct experience supporting a Customer Success or Post-Sales organization. Worked alongside CS leadership, understand the mechanics of retention and expansion, and have driven measurable impact on GRR, NRR, or churn.
Hands-on with a CS platform. Deployed, administered, or deeply operated a CSP. Understand health scoring, playbooks, and lifecycle workflows.
Strong technical and analytical instincts. Write your own SQL, build your own models, and work directly with operational data.
Enterprise product experience. Worked on a product sold to Enterprise customers.
Structured thinking and commercial judgment. Work is rigorous, priorities are clear, and build for impact.
Exceptional communication. Move from a SQL query to an exec-level recommendation in the same hour.
Genuine, daily AI fluency. Built skills, agents, or automated workflows that others use.
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