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About the Role
As part of the growing Data Science and Analytics team, you will drive data-informed decision making across the organization to support the mission of building safe and beneficial artificial intelligence. You will apply your experience to shape the cultural norms and best practices of a growing data science team as Anthropic scales. Your work will be critical to informing strategy as the company deploys safe, frontier AI at scale.
Responsibilities
- Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through insights and recommendations.
- Develop hypotheses, apply rigorous causal inference methods (controlled experiments, synthetic controls), and analyze results to 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 analytics infrastructure to support rapid iteration and decision-making as products grow.
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.
- Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem.
Skills
- Python
- SQL
- Data visualization
- Experimental design
- Causal inference
- Statistical modeling
- A/B testing
- Written communication
- Presentation skills
- AI/ML products
- Large language models
- Developer tools
Location
- San Francisco
Work Type
- Hybrid
Experience Level
- 7+ years
Education Level
- Bachelor’s degree or equivalent combination of education, training, and/or experience
Salary/Compensations
- $285,000—$380,000 USD
Benefits
- Competitive compensation
- Optional equity donation matching
- Generous vacation
- Generous parental leave
- Flexible working hours
- Lovely office space
About the Company
- Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society.
- The team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders.
- The company believes that the highest-impact AI research will be big science, working as a single cohesive team on large-scale research efforts.
- Anthropic values impact—advancing long-term goals of steerable, trustworthy AI—rather than work on smaller puzzles.
- AI research is viewed as an empirical science with commonalities to physics and biology.
- The company is an extremely collaborative group hosting frequent research discussions.
- Anthropic is a public benefit corporation headquartered in San Francisco.
Equal Opportunity
- We encourage you to apply even if you do not believe you meet every single qualification.
- Not all strong candidates will meet every single qualification as listed.
- Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.
- We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.