Data Scientist, Product

Anthropic•Seattle, WA

8d•$285,000 - $380,000•Hybrid

About The Position

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.

Requirements

7+ 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

Nice To Haves

Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem

Responsibilities

Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your 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
Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success
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