Data Science Manager, Anthropic

• MS or PhD in a quantitative field (statistics, mathematics, computer science, physics, or related)
• 8+ years of experience in data science and analytics, including 4+ years managing high-performing data teams
• Proven track record of driving product strategy through data insights and building metrics that matter
• Deep expertise in statistical analysis, experimental design, and causal inference
• Experience with SQL, Python, R, and data visualization tools for large-scale analysis
• Demonstrated ability to partner effectively with cross-functional stakeholders and influence decision-making through data
• Experience building data capabilities from early stages through rapid growth phases
• Strong communication skills, with ability to translate complex technical concepts to diverse audiences
• Passion for Anthropic's mission of building safe and beneficial AI

Desirable

• As a Data Science Manager at Anthropic, you will be responsible for building, mentoring and leading a world-class team that turns data into actionable insights
• This extremely impactful role is central to scaling our business while maintaining our commitment to safe and beneficial AI
• You and your team will develop metrics, analyses, experiments, and machine learning models that help create excellent user experiences and grow the business
• You'll collaborate closely with go-to-market, finance, infrastructure, research, and product teams to guide our strategic decision-making as we deploy frontier AI technology to users worldwide
• As a key leader of Anthropic's data strategy, your team's work will shape key decisions, directly accelerate our progress, and contribute to Anthropic's mission of ensuring that artificial intelligence has a positive impact on humanity
• Lead and develop a high-performing team of data scientists, providing mentorship, guidance, and career development opportunities
• Partner with Sales, Marketing, Compute, and Finance leadership to develop metrics, dashboards, and analyses that inform strategic decisions across these domains
• Drive product strategy through data-driven insights, including user behavior analysis, product performance metrics, causal inference and experimentation
• Create and maintain sophisticated forecasting models for business planning, operations and capacity management
• Develop lead scoring, customer segmentation, propensity models, and predictive machine learning approaches to help nurture and grow customer accounts
• Establish engineering best practices, data modeling and scalable data infrastructure in collaboration with engineering teams
• Communicate complex analyses and recommendations effectively to executives and stakeholders across the organization
• Foster a collaborative, inclusive team culture that balances technical excellence with practical business impact