Basis AI

Basis AI

Revenue Operations Leader

New York Office

Sponsorship not specifiedDetected 43 days ago
Machine LearningHubSpotSalesforceCRMAccountingForecastingValuationCadenceLeadershipVariance Analysis

About the role

  • Our agents operate for hours at a time, performing end-to-end work for some of the largest accounting firms in the world.
  • We recently raised $100M at >$1B valuation and are racing to deploy the most advanced applied ML at production scale.
  • They've pushed the limits of what we thought our models could do on real-world, economically valuable, complex accounting tasks.

Responsibilities

  • Build & lead the rev ops team
  • Recruit, hire, and develop a high-performing rev ops team across systems administration, data/analytics, deal desk, and commissions
  • Create a culture of rigor, speed, and cross-functional partnership
  • Own systems & data
  • Own and optimize the GTM stack (Salesforce/HubSpot, Outreach, Apollo, Clay, automation platforms)
  • Build dashboards and analytics that leadership and teams trust for decision-making
  • Design integrations and workflows to maintain clean, reliable data across tools
  • Drive execution & alignment
  • Build and maintain integrations and automation to increase rep productivity
  • Standardize lead-to-customer lifecycle and implement scalable pipeline governance

Compensation

  • Translate company growth targets into quarterly and annual GTM operating plans with clear goals and leading indicators

Benefits

  • Pre-tax commuter benefits and 401(k) retirement plan
  • Parental Leave
  • Premium Medical, Dental, and Vision coverage; Life Insurance; and 6 coaching & 6 therapy sessions through Spring Health.
  • Unlimited PTO + 12 paid company holidays.
  • Partner with CEO and Sales/Marketing leadership on segmentation, territory design, pipeline health, and forecasting

Company info

  • We're looking for a Revenue Operations Leader to build, lead, and scale the rev ops function at Basis.

This listing is sourced directly from Basis AI's careers page and normalized into a canonical job model.