Anthropic
Data Scientist, Developer Productivity
About this role
Anthropic seeks a Data Scientist to establish how developer productivity is measured and improved in an AI-first organization. You'll partner with engineering leadership to define metrics, run experiments on tooling changes, and build the analytical foundation that drives infrastructure investment decisions in a rapidly evolving space.
What you'll do
- Lead investigations into ambiguous questions like how AI tools impact engineer velocity and what 'productivity' means in this context
- Define and implement a metrics framework for developer productivity in AI-augmented workflows
- Design and execute experiments on internal tooling and workflow changes to establish causal evidence
- Build analytical pipelines, dashboards, and models to instrument productivity measurement
- Partner with engineering leadership to set the measurement agenda and research priorities
- Influence leadership decisions with data, openly challenging narratives when evidence doesn't support them
What they're looking for
- Production SQL and Python (or equivalent language)
- Data pipeline and dashboard development
- Experimental design and causal inference
- Metric definition and framework design
- Data storytelling and stakeholder communication
- Statistical analysis and modeling
- Ability to work in ambiguity and iterate quickly
- Understanding of developer tools and workflows
Benefits
- Work at the intersection of data science, developer experience, and frontier AI
- Opportunity to define a new measurement discipline from the ground up
- Hands-on technical role with direct impact on engineering infrastructure
- Located in San Francisco, CA or New York City, NY
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Anthropic
Anthropic builds Claude, an AI assistant, and is hiring for engineering roles across infrastructure, data systems, and security that support both AI research operations and the company's internal technology needs. The company seeks infrastructure engineers, systems integrators, data scientists, and security specialists to build production-scale systems for training data pipelines, financial operations, developer productivity measurement, research infrastructure, and server firmware security.
- Website
- anthropic.com
Likely interview questions
- Tell us about a time you had to define a metric or measurement framework when the problem wasn't well-understood—how did you approach it?
- Describe a project where you designed an experiment to measure impact. How did you establish causality?