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Replay

Founding Account Executive, Data Partnerships

New York, United States

Location
New York, United States
Work
Not stated
Employment
Full-time
Level
Not stated
Function
Data & AI
Pay
$225K – $300K a year (read from the ad)
Posted
3 months ago

About the role

About Replay

We are building the first-ever bank for enterprise data. There are over 35 million businesses in the US alone, many of which are sitting on an asset they don’t know they have. At Replay, we help businesses monetize their historical operating data by licensing it to the frontier AI and data labs for model training. Replay sits at the intersection of advancing the frontier of AI, while helping companies generate millions in growth capital without having to give up equity, take on debt, or lay off employees.

Why join Replay now

  • We've scaled from $0 to a multi eight-figure run rate in a matter of months
  • We've raised from top-tier investors (Floodgate, Afore, Ludlow, Hustle Fund, etc.)
  • We're small enough that you'll carry outsized responsibility and grow as fast as the company does
  • You'll partner and build for the fastest and most important companies in the world
  • You'll be a part of building a massive, category-defining business from the ground floor

The Role

As an Account Executive (Data Partnerships), you'll source the real-world business data that trains the next generation of AI models directly from operating companies. Unlike our Wind-down motion, there's no forcing event here pushing a company toward yes. You're selling a new, no-catch revenue stream: companies license their data, retain ownership of it, we de-identify it, and they get paid. You'll identify, pitch, negotiate, and close these deals end-to-end, translating between what makes a dataset valuable to AI labs and what actually gets a company to say yes.

What You'll Do

  • Own the full lifecycle: source targets, pitch executives, structure terms, and close proprietary data deals
  • Structure and negotiate complex deal structures; handling pricing, terms, data privacy, anonymization, and compliance
  • Speak with and manage C-suite executives through complex sales cycles
  • Work with with engineering, ops and our partners to identify the most valuable assets that need sourcing

How You'll Be Measured

  • Number of datasets closed per month
  • Percentage of pipeline self-sourced
  • Percentage and ratio of higher value datasets acquired

Required aptitude

  • You're excited about building in-person, 5 days a week, from our office in Dumbo
  • You want to work hard and strive for world-class levels in performance
  • 4-6+ years in a high-performance, client-facing environment: enterprise sales, consulting, investment banking, partnerships, business development, or data deals
  • A track record of hitting or exceeding a number (quota, revenue, deals closed) that you can point to concretely
  • Banker/M&A-caliber negotiation skill: handles objections and is comfortable in high-stakes, high-scrutiny conversations
  • High EQ and IQ, technically credible enough to speak to highly technical mechanics with engineering and legal stakeholders

Bonus

  • Experience in data licensing, sourcing, or selling data
  • Previously worked at an AI lab, data labeling company, top-tier management consulting firm, or investment bank
  • Background in complex B2B negotiations or structured finance/deal-making

Compensation & Benefits

  • OTE: $225K - $300K
  • Annual Bonus in addition to OTE
  • Meaningful equity
  • 100% covered medical, dental, and vision
  • Unlimited PTO
  • Free gym + workout class memberships (via Wellhub)
  • $500 desk allowance
  • Up to $15,000 relocation bonus as applicable

How We Hire

  1. Intro Chat (20 min): mutual fit and interests
  2. Mock Pitch (1hr): sell us something
  3. Take home: prepare a short case study
  4. Onsite (3 hrs): present your case study, meet the team, have snacks
  5. References -> Offer

Source

Posted by Replay on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 06:17 UTC; the original is the reference.

View the original ad ↗

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