Data Scientist - AI Safety

Job summary

Responsibilities

We're looking for a Data Scientist to take ownership of the datasets and evaluation workflows that underpin our AI Safety work. You'll turn real-world product data into reliable, well-structured datasets for training and evaluating models, and help build the processes and infrastructure to…

• Own safety datasets end-to-end: collection, cleaning, labelling, quality control, versioning, and readiness for training and evaluation.
• Translate safety policy into clear, consistent labelling and evaluation criteria, working closely with policy specialists.
• Design and manage labelling processes, including sourcing, onboarding, and overseeing external contributors to a high quality bar.
• Build evaluation workflows for models in production, using real-world data to track performance and surface issues.
• Develop lightweight Python/SQL pipelines and tooling to make data work faster and reproducible, partnering with ML engineers on what "training-ready" looks like.

What they're looking for

• Experience as a Data Scientist, or similar, working with real-world datasets and ML models.
• Strong grasp of what makes a good dataset: collection, cleaning, sampling, labelling, quality control, evaluation.
• Comfortable with Python and SQL for analysis and practical data workflows.
• Strong critical thinking and judgement - comfortable with ambiguity and nuance, and able to turn complex guidelines into consistent, scalable decisions.
• Autonomous and a clear communicator, able to work across disciplines (policy, engineering, research) in a fast-moving, still-forming environment.

Tech stack

• Python
• SQL