AI Safety Data Scientist - Datasets & Evaluation

ElevenLabs; Greater London; On-site; GBP 90,000 - 110,000; Full time

Job summary

ElevenLabs is hiring a Data Scientist to own the datasets and evaluation workflows underpinning our AI Safety work. You’ll turn real-world product data into reliable, structured datasets for training and evaluating models, and build scalable data processes with policy and engineering teams.

This hands-on role combines data science, ML, AI safety, and policy, starting with collection, labelling, and analysis, then establishing evaluation systems and contributor networks for scale.

Qualifications

• Experience as a Data Scientist, or similar, with real-world datasets and ML models.
• Strong grasp of dataset quality: collection, cleaning, sampling, labelling, quality control, evaluation.
• Comfortable with Python and SQL for analysis and practical data workflows.
• Strong critical thinking and judgement - able to handle ambiguity and translate guidelines into decisions.
• Autonomous and clear communicator, able to work across policy, engineering and research.

Responsibilities

• 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.

Skills

Data Science

Python

SQL

Labelling

Experimentation

Communication

Tools

Python (Pandas)

SQL

Pandas

Labelling tools

Job description

ElevenLabs is hiring a Data Scientist to own the datasets and evaluation workflows underpinning our AI Safety work. You’ll turn real-world product data into reliable, structured datasets for training and evaluating models, and build scalable data processes with policy and engineering teams.

This hands-on role combines data science, ML, AI safety, and policy, starting with collection, labelling, and analysis, then establishing evaluation systems and contributor networks for scale.