AI Hiring Index

Anthropic · Data · Senior · Posted 2026-05-31

Data Scientist, GTM

Anthropic · New York City, NY; San Francisco, CA | New York City, NY · $285k–380k base

This range's midpoint is above 89% of posted data ranges at AI companies right now. See the salary index.

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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 & 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.

Key responsibilities

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

Minimum qualifications

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

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $285,000 — $380,000 USD

Logistics

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 t …

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