Arbor

Arbor

Growth Lead

New York City

Sponsorship not specifiedDetected 97 days ago
A/B TestingSalesForecastingLogistics

About the role

  • WE UNLOCK GROUND TRUTH FOR THE ENTERPRISES THAT POWER THE GLOBAL ECONOMY.
  • Until today, those conversations vanished into thin air the second they happened.
  • Arbor turns in-person conversations into executive-grade strategic intelligence.

Responsibilities

  • You'll report directly to the CEO and own the systems and instincts that turn our early traction into a repeatable, scalable revenue engine.
  • Backgrounds from Harvard, Princeton, Meta, Insight Partners, IBM.
  • We know how to listen, build, sell, ship, scale - then iterate and accelerate.

Requirements

  • You are equal parts strategist, operator, and builder.

Nice to have

  • You keep pipeline clean, forecasting accurate, and conversion data visible and actionable.
  • You enable our sales team to run at full speed.
  • You identify the highest-leverage channels, run experiments fast, and double down on what works - whether that's content, partnerships, events, or something we haven't tried yet.
  • Thinks in systems, not tasks.
  • You connect the dots between marketing signals, sales behavior, and revenue outcomes.
  • You see the full funnel and know where it's leaking.
  • Is obsessed with data.
  • You don't guess.

Benefits

  • Already backed by the best with $6M+ from 645 Ventures, NextPlay Ventures (Jeff Weiner), Wisdom, and angels, but early enough for founding team members to see generational outcomes from equity.

Company info

  • We're already working with multi-billion dollar manufacturers, retailers, and logistics companies.
  • Customers see immediate ROI.
  • Enterprise deals close fast.
  • Mostly importantly, join for the team.
  • There are billions of important conversations taking place in real time each day in hospitality, food service, retail, logistics and countless other industries - conversations with employees and conversations with customers.

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