Anthropic· Data Science & Analytics· San Francisco, CA | New York City, NY
Data Scientist, Developer Productivity
Classified Tasks (27)
Automate 4%Augment 67%Human-Only 30%
Automate (1)
Fully handled by AI agents
Maintain core reporting to evaluate developer productivity and engineering effectiveness
administrative
Augment (18)
AI assists, human decides
Define key metrics to evaluate developer productivity and engineering effectiveness
analytical
Build measurement frameworks to assess developer productivity and engineering effectiveness
analytical
Deep dive into product and user data to derive actionable insights
analytical
Size opportunities based on data analyses
analytical
Develop hypotheses about developer productivity and tooling impacts
analytical
Design and apply rigorous causal inference methods, including controlled experiments and synthetic controls, to make actionable recommendations
analytical
Investigate anomalies in product and engineering metrics
analytical
Conduct root cause analyses to identify underlying issues in engineering workflows
analytical
Provide data-driven insights to guide priorities and inform decisions
analytical
Build statistical models to support analysis and decision-making
analytical
Build optimization frameworks to improve operational processes
operational
Build simulations to automate decision-making and operational processes
operational
Scale analytics infrastructure to support rapid iteration as products grow
technical
Study frontier AI usage by engineers and analyze AI-augmented development workflows
analytical
Quantify where tooling investments pay off
analytical
Analyze how AI-assisted development is changing the shape of engineering work
analytical
Provide analyses to inform infrastructure priorities
analytical
Provide analyses to inform tooling roadmaps
analytical
Human-Only (8)
Requires human judgment
Influence product and tooling roadmaps through clear recommendations
leadership
Present complex analyses and recommendations to technical and non-technical stakeholders
communication
Establish foundational data practices for the analytics team
leadership
Drive data-informed decision making across the company
leadership
Own the quantitative foundation for how engineers build, identifying blockers and accelerators
operational
Inform strategies for scaling engineering output as the company grows
leadership
Help shape cultural norms and best practices of the data science team
leadership
Engage with builders (engineers) as users to collect feedback and inform tooling and analytics decisions
communication
Job description
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. Data Scientist, Developer Productivity About the role 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. Key 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 Minimum qualifications 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 Preferred qualifications 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 helpfu