Lead Data Scientist, Platform Product

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

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.

Key responsibilities

• 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

Minimum qualifications

• 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 recommenda