Senior Frontier Data Strategist
Scale AI
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What strategist roles keep asking for: Paid media (21%), Stakeholder management (19%), B2B (13%) — counted across their open postings here.
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Preparing for this interview
Interviews for strategist roles keep coming back to Paid media, Stakeholder management, B2B. Practise those questions before you sit with Scale AI.
Questions you are likely to be asked
- Why do you want to join Scale AI?
- What is your experience with Customer success? Tell me one thing you learned the hard way.
- Tell me about a problem you solved at work that you are proud of.
- Tell me about a time you disagreed with your manager. What happened?
- Where do you want to be in three years?
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Practise the Senior Frontier Data Strategist at Scale AI interview free →Frontier AI labs decide what direction their models need to take before the actual training starts. As a Senior Frontier Data Strategist on Scale's Generative AI team, you'll be a trusted voice in those decisions. You'll partner with research leads and senior stakeholders at the world's leading AI labs to shape the data strategy behind their next generation of models, then design the human-data programs to deliver it.
You'll sit where frontier research meets Scale's product roadmap, and you'll be expected to move both. With customers, you'll own senior, technically grounded relationships, anticipate where their research is heading, and bring them new data ideas before they ask. Inside Scale, you'll be a leading voice with our AI Product Managers, ML Research, Delivery Operations, and Engagement Management teams, turning what you learn from customers into product priorities and investment decisions.
This is a forward-looking, highly cross-functional role. Our Engagement Managers own customer success for live programs; Frontier Data Strategists own everything that comes before it: spotting the need, designing the program, scoping and forecasting it, and winning the work. As a senior member of the team, you'll set the standard for how Scale does this work and help develop the Frontier Data Strategists around you.
What you’ll do:
- Own relationships with senior research stakeholders at your assigned frontier labs, such as research leads, heads of post-training, and technical leadership, and become a strategic thought partner on their post-training, evaluation, and agent roadmaps.
- Set the data strategy for your accounts: anticipate needs across research areas, spot where the biggest opportunities are, and build a multi-program plan for how Scale can help.
- Direct the cross-functional team designing Scale's most complex and novel human-data programs, including work that has no precedent at Scale.
- Shape Scale's product roadmap by representing your customers in planning with AI Product Managers and ML Research, and by resolving tradeoffs between customer needs and what Scale can build.
- Bring insights from the frontier (research directions, emerging data needs, capability gaps) back to Scale's leadership and technical teams to guide strategy and investment decisions.
- Own the pipeline of new opportunities for your accounts. Lead scoping, forecasting, and pricing with Delivery, Growth Operations, and Finance, and see the work through to signed programs and a clean handoff.
- Mentor Frontier Data Strategists, set the bar for program design and customer engagement, and help build the playbooks the team runs on.
What we’re looking for:
- 5+ years in a technical AI/ML role, such as ML engineering, research, applied science, technical product management, or post-training data work at a lab or data provider.
- Deep fluency in the LLM training lifecycle, especially post-training: SFT, preference data, reward modeling, RL environments, evaluations, agentic training, etc.
- A track record of owning relationships with senior technical stakeholders, and of influencing their direction through substance.
- Evidence of shipping ambiguous, high-stakes technical programs from idea to delivery.
- Experience influencing a product or research roadmap without direct authority.
- The ability to read a research paper and form an opinion on what data would improve a given capability, and to defend that opinion to researchers.
- A degree in CS, engineering, math, physics, or another quantitative field.
Ideally you'd have:
- Hands-on experience designing training data, evals, or RL environments.
- A graduate degree (PhD, MS) or published research in ML or a related field.
- Experience at a frontier lab, model developer, or AI data company.
- Experience mentoring or leading technical teammates, formally or informally.
- A background in founding or leading at an early-stage startup, or in pre-sales, solutions engineering, or technical consulting.
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 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.
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Listed on greenhouse · posted 2026-04-20. ApplySarthi collects openings and links to application pages; the role is advertised by Scale AI, not by us.