Sr. Data Scientist, GenAI & Labeling Platforms
About The Position
Pinterest is looking for a Senior Data Scientist to join their GenAI & Labeling Platforms team. This role focuses on advancing the science and systems behind labeling, evaluation, and GenAI-enabled workflows. The work involves LLM-assisted labeling, human-in-the-loop quality systems, prompt and rubric design, model evaluation, and methods for improving the speed, consistency, and usefulness of judgment-based data. The ideal candidate will be a strong individual contributor who can execute high-impact technical work, partner cross-functionally to implement durable platform capabilities, and grow with the team in a rapidly evolving space.
Requirements
- 6+ years of combined post-graduate academic and industry experience (or PhD + 3 years) applying scientific methods to real-world problems on large-scale data
- Strong hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems
- Experience applying LLMs or other generative AI techniques to practical workflows, systems, or products
- Ability to turn ambiguous problems into rigorous analyses, experiments, and prototypes
- Track record of writing high-quality code and using technical work to influence product or platform direction
- Solid cross-functional collaboration skills and experience working effectively across teams
- Business and product sense with the ability to define meaningful success metrics
- Self-directed learning mindset and comfort working in a rapidly evolving technical landscape
Nice To Haves
- Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred
Responsibilities
- Execute high-impact scientific work across GenAI-powered labeling and evaluation systems
- Identify opportunities where LLMs and related methods can improve quality, speed, coverage, and cost efficiency
- Develop prototypes that demonstrate value in areas such as prompt optimization, task decomposition, quality estimation, routing, and human-in-the-loop workflows
- Design experiments and measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs
- Partner with engineering, product, and data science teams to productionize successful approaches
- Apply standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight
- Contribute to reusable methods and frameworks that can scale across teams and use cases
- Support more junior scientists and contribute to the technical health of the team
Benefits
- Flexibility to do your best work
- Career growth opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
