Growth Data Scientist: Personalization & Experiments

Anthropic; New York, Seattle, San Francisco (NY, WA, CA); Hybrid; USD 285,000 - 380,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation and parental leave

Flexible working hours

Office space

Job summary

Anthropic is seeking a data science leader to join the Growth team, focusing on personalization and how Claude informs user experiences across onboarding, lifecycle, and in-product messaging.

You’ll design experiments, build targeting models, and develop metrics that connect short-term actions to long-term value. Strong Python/SQL skills and a track record in production ML are essential.

Qualifications

• Bachelor’s degree or equivalent in a relevant field
• Minimum education: Bachelor’s degree or equivalent combination of education, training and/or experience
• Minimum years of experience will correlate with internal job level requirements for the position

Responsibilities

• Build and ship targeting and personalization models
• Design tests to evaluate personalization strategy
• Analyze A/B tests and quasi-experiments
• Develop metrics and guardrails linking short-term wins to long-term value
• Experience applying data science to growth, lifecycle, or personalization problems
• Experience building and shipping ML models that drive user-facing decisions
• Experience with experimental design and causal inference, including A/B testing at scale
• Proficiency in Python and SQL
• Communicate analysis in writing and influence priorities across teams
• Prioritize when requirements are unclear or changing
• Interest in Anthropic’s mission of building safe and beneficial AI

Skills

Contextual bandits

Lifecycle personalization

Experimentation platforms

LLMs / coding agents

Communication of analyses

Education

Bachelor’s degree

Tools

Python

SQL

Job description

Anthropic is seeking a data science leader to join the Growth team, focusing on personalization and how Claude informs user experiences across onboarding, lifecycle, and in-product messaging.

You’ll design experiments, build targeting models, and develop metrics that connect short-term actions to long-term value. Strong Python/SQL skills and a track record in production ML are essential.