About this role
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 an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You bring experience from high-bar teams and are eager to help shape the norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.
You’ll be the senior data science leader embedded in our Developer Platform product team and a strategic thought partner to its product leads. You’ll help set product direction for the Claude Developer Platform, spanning our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You’ll bring a point of view on where to invest, how to grow our platform business, and how to deliver more value for the developers and enterprises building on Claude. As a tech lead manager, you’ll also manage a small team of Product Data Scientists, setting their agenda and raising the bar for how data shapes product decisions.
Responsibilities:
• Act as a strategic thought partner to Developer Platform product leads, helping shape product strategy, roadmap priorities, and the major bets the team makes
• Set the data science agenda for Developer Platform, deciding where the Product Data Science team can have the most impact and what it should deprioritize
• Manage and develop a small team of Product Data Scientists, coaching them to move from answering questions to shaping decisions
• Frame the most important and ambiguous questions facing the platform, from how developers and enterprises adopt it to how AI agents are being built and deployed at scale, size the opportunities, and make clear recommendations, including when they challenge the current direction
• Define how Developer Platform measures success, establishing the core metrics and measurement frameworks that align teams and leadership on what matters
• Set the standard for experimentation and causal inference across Developer Platform, including where API and B2B products make clean experiments hard, and personally lead the highest-stakes analyses
• Turn complex analyses into clear narratives and recommendations that drive decisions with senior leadership and cross-functional partners, including go-to-market teams
• Establish foundational data practices and shape the analytics infrastructure Developer Platform needs to support rapid iteration and decis