Sr. Data Scientist, GenAI & Labeling Platforms

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

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.

 

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