Lead Data Scientist, Platform Product at Anthropic

Hybrid - New York City, NY; Seattle, WA; San Francisco, CA

Apply
More jobs at Anthropic

As part of our growing Data Science and Analytics team at Anthropic, you will drive data‑informed decision‑making across the organization. You will partner with product, engineering, and go‑to‑market teams to understand how AI agents are built and deployed at scale, identify growth opportunities, surface actionable insights, and shape our platform roadmap. In this hybrid role, you’ll define key metrics, conduct deep dives into usage data, develop hypotheses with rigorous causal inference methods, investigate anomalies, build statistical models, and present findings to stakeholders. You’ll also help establish foundational data practices and scale analytics infrastructure to support rapid iteration as the platform grows.

Salary

USD 285,000 - 380,000

Requirements

Skills

  • 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
  • 6+ years of experience in data science or analytics roles
  • Experience supporting B2B sales teams with data insights
  • Strong instincts for what drives product adoption, engagement, and retention in developer or enterprise contexts
  • Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem
  • Comfort operating in ambiguous, fast-moving environments where creating clarity is part of the role
  • A genuine interest in Anthropic's mission of building safe and beneficial AI

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

Technologies

PythonSQLData visualization toolsExperimental designCausal inference methodsStatistical modelingA/B testingAPIDeveloper-facing productsLarge language models

Share job

See if your resume is ready for this job

See how our AI can optimize your resume and improve your chances for this role.