Anthropic is looking to shape the future of AI-powered developer tools by improving the Claude Code product, a command line tool that enables developers to delegate coding tasks directly to Claude from their terminal. The goal is to understand developer interaction with AI coding assistants, measure the impact of the tool on developer productivity, and identify opportunities to enhance the developer experience.
Requirements
- Have 5+ years of experience in data science or analytics roles with significant focus on product analytics
- Have experience working with developer tools, IDEs, command line interfaces, or other technical products used by software engineers
- Have expertise in Python, SQL, and data visualization tools, with comfort working in command line environments
- Have experience measuring productivity, engagement, and satisfaction metrics for technical users or B2B products
- Have experience turning complex technical usage patterns into clear, actionable insights for product and engineering teams
- Experience with software development workflows, version control systems, and common developer tools
- Familiarity with AI/ML model outputs and experience analyzing human-AI interaction patterns
Responsibilities
- Deep dive into how developers use Claude Code across different programming languages, project types, and workflows to provide insights that inform product strategy and feature development
- Design and implement metrics to quantify how Claude Code affects developer productivity, code quality, and development velocity across different use cases and skill levels
- Analyze patterns in human-AI collaboration within coding workflows, identifying opportunities to improve the handoff between developers and Claude for more effective task delegation
- Develop hypotheses about product changes, design controlled experiments with developer users, and analyze results to guide feature prioritization and development
- Identify friction points in the Claude Code user journey and provide data-driven recommendations to improve onboarding, retention, and long-term engagement
- Build robust measurement frameworks to understand CLI adoption patterns, feature utilization, and user segmentation across different developer personas and organizations
- Partner with engineering to build experimentation capabilities tailored to developer tools, accounting for the unique challenges of measuring productivity and satisfaction in coding workflows
Other
- Are passionate about AI-assisted development and excited about the potential for AI to enhance developer productivity and creativity
- Possess strong instincts for what drives developer adoption and retention of technical tools
- Have a bias for action and pragmatism, comfortable making decisions with incomplete information in a fast-moving environment
- Thrive in ambiguity and take initiative to create clarity and drive progress on undefined problems
- Demonstrate exceptional written communication skills and ability to present findings to technical and non-technical stakeholders
