> Markdown version of [/jobs/ext/4585037-data-scientist-gtm](https://www.wearedevelopers.com/jobs/ext/4585037-data-scientist-gtm). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist, GTM - **Company:** Anthropic Limited - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $275,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Data Visualization, Programming Tools, Python (Programming Language), SQL Databases, Large Language Models, AI Platforms, Data Analytics - **Published:** November 5, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-scientist-gtm-san-francisco-ca--aada6247-91f3-4931-b4cd-da462b44ba15 ## About the Role Data Science, Artificial Intelligence (AI), Statistics, Data Science, Sales Operations, Market Share, Data Analysis, Analysis Skills, Best Practices, Metrics, * Proficiency in Python, SQL, and data visualization tools * Expertise in experimental design, causal inference, statistical modeling, and A/B testing, particularly in high-scale technical environments * Demonstrated ability to translate complex data into clear, actionable insights for both technical and business audiences * Strong written communication and presentation skills * Ability to work effectively in fast-moving, ambiguous environments - comfortable creating structure and driving progress where neither yet exists Preferred qualifications * 5+ years of experience in data science or analytics roles * A strong track record in multi-segment, multi-product B2B sales or commercial analytics, especially with consumption-based revenue models * Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem * Genuine interest in Anthropic''s mission of developing safe and beneficial AI, Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. ## Description As part of our growing Data Science & Analytics team, you will play an instrumental role in Anthropic''s mission of building safe and beneficial AI - this time by driving data-informed decisions across the commercial customer lifecycle. This role sits at the intersection of fast-moving sales operations and rigorous statistical analysis. You will work across multiple segments and products, partnering with analytics engineers, fellow data scientists, and go-to-market leadership to turn complex commercial data into actionable strategy. You will own measurement and analysis for new logo acquisition through activation, expansion, and retention for a rapidly scaling, consumption-based AI platform. You''ve worked in cultures of analytical rigor before, and you''re eager to help shape the norms and best practices of a growing data science function at a pivotal moment in the company''s growth., * Define key metrics, build measurement frameworks, and maintain core reporting to evaluate GTM success across segments and products * Analyze commercial and user data to surface actionable insights, size opportunities, and influence roadmaps and go-to-market strategy * Develop hypotheses and apply rigorous causal inference methods - controlled experiments, synthetic controls - to make clear, actionable recommendations * Investigate anomalies, conduct root cause analyses, and provide data-driven guidance on priorities and decisions * Build statistical models, optimization frameworks, and simulations to support and automate commercial decision-making processes * Present analyses and recommendations to both technical and non-technical stakeholders, including GTM leadership * Establish foundational data practices and help scale analytics infrastructure to support rapid product and commercial iteration