Sr.DataScientist,GenAI&LabelingPlatforms
“Sr. Data Scientist, GenAI & Labeling Platforms at Pinterest. Skills: GenAI-powered labeling and evaluation systems, LLMs, human-in-the-loop quality systems, prompt and rubric design, model evaluation, methods for improving the speed, consistency, and usefulness of judgment-based data. 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”
Industry & Context.
turn ambiguous problems into rigorous analyses, experiments, and prototypes; rigorous analyses
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., US based applicants only
What They're Looking For.
Must Have
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, hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems, 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 Have
Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred, PhD + 3 years experience
What You'll Do.
Execute high-impact scientific work across GenAI-powered labeling and evaluation systems
Identify opportunities where LLMs and related methods can improve quality
Develop prototypes that demonstrate value in areas such as prompt optimization
and human-in-the-loop workflows
Design experiments and measurement frameworks to evaluate model performance
and operational tradeoffs
Partner with engineering
and data science teams to productionize successful approaches
Apply standards for trustworthiness
including bias measurement
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
How You'll Work.
Team & Collaboration
partner cross-functionally to turn successful ideas into durable platform capabilities; Partner with engineering, product, and data science teams to productionize successful approaches; Solid cross-functional collaboration skills and experience working effectively across teams
Communication Scope
explain your approach; showing us not just what you know, but how you think
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