Data Scientist, Developer Productivity

Anthropic•San Francisco, CA

12h•Hybrid

About The Position

As part of our growing Data Science and Analytics team, you'll play an instrumental role in Anthropic's mission of building safe and beneficial AI by driving data-informed decision making across the company. This role sits at the intersection of data science, developer experience, and AI tooling — and offers the unusual opportunity to study frontier AI usage from the inside, with the builders themselves as your users. You'll define how Anthropic understands and improves developer productivity — both through classic software engineering effectiveness measures and through the emerging challenge of understanding AI-augmented development workflows. You'll own the quantitative foundation for how Anthropic's engineers build: what slows them down, what accelerates them, where tooling investments pay off, and how AI-assisted development is changing the shape of engineering work. Your analyses will directly inform infrastructure priorities, tooling roadmaps, and how we think about scaling engineering output as Anthropic grows. You've worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale.

Requirements

Working expertise with Python and SQL
Working expertise with data visualization tools
Hands-on experience with experimental design, causal inference, statistical modeling, and A/B testing frameworks
Strong written communication and presentation skills
Track record of translating complex data into clear, actionable insights for both technical and business stakeholders

Nice To Haves

7+ years of experience in data science or analytics roles
Direct experience working with developer productivity, infrastructure, performance, or platform teams in rapidly scaling environments
Deep understanding of distributed systems, cloud infrastructure, and performance engineering, with experience analyzing large-scale system metrics
Experience applying experimental design and causal inference methods in high-scale technical environments
Comfort with ambiguity and a track record of creating clarity and driving progress in fast-moving environments
Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem
Passion for Anthropic's mission of building helpful, honest, and harmless AI

Responsibilities

Define key metrics, build measurement frameworks, and maintain core reporting to evaluate developer productivity and engineering effectiveness
Deep dive into product and user data to derive actionable insights, size opportunities, and influence roadmaps through clear recommendations
Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to 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 automate decision-making and operational processes
Present complex analyses and recommendations to both technical and non-technical stakeholders
Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration as our products grow