Sr. Data Scientist, GenAI & Labeling Platforms

Pinterest brings millions of people the inspiration to create a life they love. Advancements in Generative AI have opened up a wealth of opportunities for improvements in productivity and labeling quality, and we've only scratched the surface of its capabilities. Early results show strong promise for LLM-assisted labeling — reducing time and cost, focusing human rater efforts on higher-value problems, and improving the accuracy of our learnings.

This role focuses on advancing the science and systems behind labeling, evaluation, and GenAI-enabled workflows. The work spans 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.

We're looking for a strong senior individual contributor to execute high-impact technical work in this space, partner cross-functionally to turn successful ideas into durable platform capabilities, and grow with the team as the space evolves.

What you’ll do:

We are looking for an experienced and highly capable Data Scientist to help us drive step function improvements in our data labeling capabilities at Pinterest. In this role, you will:

• 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

What we’re looking for:

• 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
• Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred

Relocation Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

In-Office Requirement Statement:

• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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