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Senior Account Executive, Data Partnerships

ABOUT SUNSET

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Sunset New York Source published Sep 20, 2026 Verified 13 hours ago
✓ 100% verification score · Source: sunset (ashby) · Always confirm final requirements on the original source.
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EmploymentFull-time

Overview

ABOUT SUNSET

Full job description

ABOUT SUNSET At its core, Sunset was founded to help founders. We started by supporting startups through shutting down, but we've since expanded into unlocking a new revenue stream for all types of businesses. In 2025, we earned a secret: the data every company generates on a daily basis (collaboration, communication, building) is some of the most valuable training data in the world. Public and synthetic can only get frontier models so far, so the next generation of model progression depends on real, proprietary data grounded in how actual businesses operate. We're a primary source of it, partnering directly with the frontier AI labs building what's next. WHY JOIN SUNSET 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 (On Target Earnings) of $420K+
  • Comprised of: $150K base + $270K+ variable
  • Meaningful equity
  • 100% covered medical, dental, and vision
  • Unlimited PTO
  • Free gym + workout class memberships (via Wellhub)
  • $500 desk allowance 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

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