Data Scientist, Anthropic

• Proficiency in Python, SQL, and data visualization tools
• Expertise in experimental design, causal inference, statistical modeling, and A/B testing, particularly in high-scale technical environments
• Experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy
• Effective written communication and presentation skills, with the ability to translate complex analyses into clear, actionable recommendations for both technical and business audiences
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Desirable

• As part of our growing Data Science and Analytics team, you will play a key role in Anthropic's mission of building safe and beneficial AI by driving data-informed decision-making across the organization. You'll be embedded with teams supporting our Developer Platform — the infrastructure that enables developers and enterprise customers to build on Claude via our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities
• In this role, you'll partner closely with product, engineering, and go-to-market teams to understand how AI agents are being built and deployed at scale.
• You'll identify growth opportunities, surface insights about platform adoption, and drive data-informed decisions that shape our platform roadmap. You'll also help establish the analytical foundations and best practices of a data science team that is still defining itself — bringing rigor and clarity to a fast-moving environment
• Define key metrics, build measurement frameworks, and maintain core reporting to evaluate platform success
• Conduct deep dives into product and usage data to surface actionable insights, size opportunities, and influence roadmaps across product, engineering, and go-to-market teams
• Develop hypotheses and apply rigorous causal inference methods — including controlled experiments and synthetic controls — to evaluate platform changes and make actionable recommendations
• Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
• Build statistical models, optimization frameworks, and simulations to support and automate operational and decision-making processes
• Present complex analyses and recommendations clearly to both technical and non-technical stakeholders
• Help establish foundational data practices and scale analytics infrastructure to support rapid iteration as the platform grows