Data Scientist
AnthropicSan Francisco, CA | New York City, NYPosted 27 February 2026
Tech Stack
Job Description
<div class="content-intro"><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h1>Job Description</h1>
<p><strong>About the role</strong></p>
<p>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.</p>
<p><strong>Core Responsibilities</strong></p>
<ul>
<li>Define key metrics, build measurement frameworks, and maintain core reporting to evaluate success</li>
<li>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</li>
<li>Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls – and analyze the results in order make actionable recommendations </li>
<li>Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions</li>
<li>Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes</li>
<li>Present complex analyses and recommendations to both technical and non-technical stakeholders</li>
<li>Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow</li>
</ul>
<p><strong>You may be a good fit if you have:</strong></p>
<ul>
<li>5+ years of experience in data science or analytics roles </li>
<li>Deep expertise with Python, SQL, and data visualization tools</li>
<li>Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments</li>
<li>Highly effective written communication and presentation skills</li>
<li>A track record of translating complex data into clear, actionable insights for both technical and business stakeholders</li>
<li>A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress</li>
<li>A passion for the company’s mission of building helpful, honest, and harmless AI</li>
<li>Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem</li>
</ul>
<h2>We’re hiring across multiple pillars</h2>
<p>Applying for this role will allow you to be considered for all pillars currently hiring. You will be asked to select a preference when submitting an application.</p>
<p><strong>Platform Product Data Scientist</strong></p>
<p>You will partner closely with product, engineering, and go-to-market teams to understand how developers and enterprise customers build on and adopt the Claude Developer Platform—spanning our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You'll identify growth opportunities, surface insights about how AI agents are being built and deployed at scale, and drive data-informed decisions that shape our platform roadmap.</p>
<p>Strong candidates may have:</p>
<ul>
<li>3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated ... (truncated, view full listing at source)
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