Data Acquisition Lead, Frontier Environments

Scale AI
San Francisco +1 more
On-siteCareer-pivot friendly

Who this role is best for

A natural match if you have experience in data licensing and AI with a senior role in commercial strategy.

Best fit for

  • Candidates with a history of creating commercial functions from scratch in AI or data markets
    — “building a commercial motion that didn't exist before you got there
  • Individuals who can bridge commercial and technical teams with domain-specific data insights
    — “technical translator between commercial and Research teams
  • Professionals skilled in negotiating complex data deals with legal and finance teams
    — “work with Scale’s legal team to define the first version of how these transactions get priced

Things to consider

  • 90-day reapplication restriction may limit flexibility for candidates needing quick next steps
    — “90-day waiting period before reconsidering candidates
  • Equity eligibility depends on Board approval, not guaranteed for all hires
    — “equity based compensation, subject to Board of Director approval

How to stand out

  • Highlight prior experience building zero-to-one commercial strategies in data-heavy industries
    — “zero-to-one function with no playbook
  • Demonstrate ability to evaluate data partnership value with technical and legal stakeholders
    — “Strong business judgment and the ability to evaluate partnership value quickly
  • Showcase hands-on pipeline development experience, not just high-level strategy
    — “Do the work by hand first, then turn what you learn into a repeatable pipeline
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · CompanyLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • mapping supply side
  • inventing deal structures
  • closing deals
Typical background
business developmentcommercial strategy

Skills & requirements

Required

Business DevelopmentCommercial StrategyDeal StructuresPartnership Management

Preferred

AI ExperienceData InfrastructureRegulated Data

Stack & domain

Business DevelopmentCommercial StrategyData LicensingCommunicationTeam CollaborationAIData InfrastructureRL Environments

About the role

Original posting from Scale AI via Greenhouse

Join the team shaping the future of AI at Scale.

Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead, you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. 

You will:

Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order.

Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced.

Close. Own it from cold outreach to signature. 

Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable.

Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline.

Ideally, you’d have:

5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there

A strong track record of managing important external relationships

Strong business judgment and the ability to evaluate partnership value quickly

Clear communication skills and comfort working with senior stakeholders

Ability to operate independently while staying closely connected to cross-functional teams

A practical, hands-on approach to building new functions from the ground up

Comfort working in fast-moving, ambiguous environments

Experience in AI, data infrastructure, marketplaces, platforms, or high-growth technology companies

Familiarity with post-training, RL, evals, or synthetic data

Experience with data licensing, IP, or regulated data

Experience partnering closely with Legal and Finance on complex agreements

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$182,400—$228,000 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision. 

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Source: Scale AI careers (Greenhouse)

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