Data Scientist

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’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. 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. The role is broad and includes responsibilities such as defining key metrics, deep diving into product and user data, developing hypotheses and applying causal inference methods, building statistical models, and presenting complex analyses.

Responsibilities

• Define key metrics, build measurement frameworks, and maintain core reporting to evaluate success.
• Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through insights and recommendations.
• Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls – and analyze the results in order 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 and decision-making as our products grow.

Requirements

• 5+ years of experience in data science or analytics roles.
• Deep expertise with Python, SQL, and data visualization tools.
• Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments.
• Highly effective written communication and presentation skills.
• A track record of translating complex data into clear, actionable insights for both technical and business stakeholders.
• A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress.
• A passion for the company’s mission of building helpful, honest, and harmless AI.
• Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem.
• At least a Bachelor's degree in a related field or equivalent experience.

Capacity Operations Data Scientist

• Experience with AI/ML operations & platforms: understanding of API rate limiting, inference workload patterns, accelerator management.
• Experience solving resource allocation problems in partnership with Finance or Operations teams.

Claude Code Enterprise Product Data Scientist

• Deep familiarity with software development workflows, developer tools, and engineering productivity metrics— ideally from working at developer-focused companies or on products targeting software engineers.
• Experience analyzing human-AI interaction patterns, particularly in code generation or developer tooling contexts.
• Experience supporting product teams building for the Enterprise.

Claude Code Marketing Data Scientist

• 3+ years of experience deeply embedding in Marketing teams, turning marketing data into concise and insightful analysis that drives business outcomes.
• Familiarity with both B2C and B2B/Enterprise marketing analytics, and a holistic view of how different marketing programs support one another.
• Experience building, selling or marketing developer tools.

Developer Productivity Data Scientist

• Direct experience working with developer productivity, infrastructure, performance, or platform teams in hypergrowth environments.
• Deep understanding of distributed systems, cloud infrastructure, and performance engineering, with experience analyzing large-scale system metrics.

Enterprise Marketing Data Scientist

• 3+ years of experience deeply embedding in Marketing teams, turning marketing data into concise and insightful analysis that drives business outcomes.
• Familiarity with both B2C and B2B/Enterprise marketing analytics, and a holistic view of how different marketing programs support one another.
• Experience working at multi-segment, multi-product B2B companies serving Enterprise customers.

GTM Data Scientist

A strong track record in multi-segment, multi-product B2B sales or commercial analytics, especially with consumption-based revenue models.

Infrastructure Data Scientist

• Experience with distributed systems and performance engineering, ideally in ML infrastructure contexts (model serving, inference latency, large-scale system metrics).
• Familiarity with SRE practices, error budgets, SLOs/SLIs, observability tools, APM systems, and infrastructure monitoring platforms (e.g., Prometheus, Grafana, DataDog).

Platform Product Data Scientist

• 3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy.
• Experience supporting B2B sales teams with data insights.
• Strong instincts for what drives product adoption, engagement, and retention.

Consumer Data Scientist

• Experience working closely with Product and Engineering teams on consumer products across multiple platforms (web, iOS, Android, desktop, browser extensions).
• Demonstrated impact on product roadmap and strategy from data deep dives in consumer growth, engagement and retention.
• Expert in experimentation, holding a high statistical bar for measuring the impact of core product changes.

Research Product Data Scientist

• 3+ years of experience deeply embedding in Product or Research teams, preferably working with LLM or AI products.
• Comfort working with unstructured data.