Rehearsals

Rehearsals

Founding Sales

New York, USA

Sponsorship not specified$110k-$140kDetected 58 days ago
DatabricksSalesNegotiationOutbound SalesResearch

About the role

  • Ask what you do, and the answer is one word.
  • We are growing fast and we need someone who can close.
  • The product wins the room once people see it.

Responsibilities

  • Own the full cycle end to end: prospecting, discovery, pitch, negotiation, signature.
  • Build your own pipeline.
  • Build the ROI case and make it land with a skeptical executive.
  • Navigate the org, manage every thread, and keep the deal moving.
  • We care deeply about what we are building and about building it together.
  • The base is lean by design and the upside is not.
  • We built this plan to be the best in the category for closers who deliver.
  • Build the playbook.

Requirements

  • You have consistently hit and beaten quota, and you can walk through exactly how.
  • Likely 5+ years selling into enterprise accounts, ideally a technical or new-category product.
  • You sell outcomes, not features, and you can hold a room of executives.
  • You can educate a buyer on a category before you convince them to buy.
  • You are either in our New York City office or out traveling to a customer.
  • You are accountable for pipeline, deal velocity, and revenue.

Nice to have

  • Experience selling into CPG, luxury, retail, consumer technology, or gaming brands.
  • A background selling AI, data, research, or analytics products.
  • Early-stage startup experience.
  • Founding or first-on-the-ground sales experience is a strong plus.

Compensation

  • Annual contract value is minimum six figures.

Benefits

  • Commission is uncapped, and the role includes equity.
  • BONUS POINTS Want to stand out?

Equal opportunity

  • Rehearsals is an equal opportunity workplace.
  • We welcome applicants of every background and identity, and we want a team where people can do their best and most authentic work.

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