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Overview
Mid-Level

Data Scientist, Marketing

Confirmed live in the last 24 hours

Anthropic

Anthropic

San Francisco, CA
Hybrid
Posted April 1, 2026

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.

About the role

As part of our growing Data Science 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.

Responsibilities:

  • Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success
  • Deep dive into marketing and user data to derive actionable insights and size opportunities to improve strategy and operations, influencing roadmaps through your insights and recommendations
  • Develop hypotheses, apply rigorous causal inference methods and analyze the results in order make actionable recommendations 
  • Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes
  • Present complex technical 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

You may be a good fit if you have:

  • 7+ years of experience as embedded DS within Marketing, Growth or GTM domains
  • Deep expertise with Python, SQL, and data visualization tools
  • Expertise with experimental design, causal inference, statistical modeling, 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
  • Exposure to AI/ML products, large language models, or developer tools in the AI/ML ecosystem

Claude Code/Cowork Marketing Data Scientist

You will partner with marketing, product, and GTM teams to understand how developers discover, adopt, and expand their use of Claude Code and Cowork —and how that individual adoption translates into enterprise deals. You'll map the full B2C2B funnel, identify where marketing can accelerate each stage, and build the experimentation muscle to test what actually moves the needle.

Strong candidates may have:

  • You have a product marketing mindset - you think in terms of user journeys, activation moments, and funnel conversion, not just campaign performance
  • Hands-on experience with B2C2B or PLG motions, and a point of view on how self-serve adoption and enterprise sales programs reinforce one another
  • A track record of surfacing opportunities others missed by connecting top-of-funnel behavior to downstream revenue
  • Experience building, selling, or marketing developer tools is a plus

Enterprise Marketing Data Scientist

You will partner with marketing and GTM teams to build the measurement foundation for Anthropic's enterprise marketing—defining what we want to learn, designing the methods to learn it, and establishing causal frameworks that tell us which marketing interventions actually drive pipeline and revenue.

Strong candidates may have:

  • Demonstrated ability to co-develop learning agendas with stakeholders and translate business questions into rigorous analytical plans
  • Fluency in causal inference and machine lear
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