Anthropic is an AI safety and research company focused on building reliable, interpretable, and steerable AI systems. This Data Scientist, Supply role addresses compute allocation and causal inference challenges to optimize resource usage and user outcomes. The position involves building metrics, analytical frameworks, and causal models, partnering with infrastructure engineers, and presenting findings to senior leadership. The work is located in San Francisco and is a full‑time, onsite role.
Data Scientist, Supply en Anthropic
Presencial - San Francisco, CA, USA
Más vacantes en AnthropicSalary
USD 285,000 - 460,000
Requirements
Skills
- Strong technical individual‑contributor background in data science, analytics, or operations research
- Demonstrated comfort reasoning about resource allocation and trade‑offs under constraints
- Working fluency with causal inference
- Deep proficiency with Python, SQL, and data visualization tools
- Track record of owning analyses end‑to‑end and communicating results clearly to engineering and product leadership
- Direct experience working closely with engineering teams on production systems
- Alignment with Anthropic's mission of building helpful, honest, and harmless AI
- 8+ years of hands‑on data science experience
- Significant technical individual‑contributor experience in data science, analytics, or operations research at staff level scope
- Experience with highly complex systems with many interacting components
- Hands‑on operations‑research depth: experience formulating and shipping real‑time constrained‑allocation, routing, or scheduling problems in production (LP/MILP, queueing, or RL‑based control)
- Causal‑inference depth beyond off‑the‑shelf quasi‑experimental templates
- Experience contributing to or designing experimentation platforms
- Exposure to AI/ML products, large language models, or large‑scale inference systems
- Track record of setting technical direction across multiple workstreams or mentoring senior individual contributors without formal management responsibility
Responsibilities
- Build and run testing frameworks—observational and synthetic—to quantify how different inputs affect compute allocation outcomes
- Connect compute allocation decisions to downstream user outcomes (retention, lifetime value, revenue)
- Partner closely with infrastructure engineers, product, and research to instrument systems, measure what matters, and ship operational changes
- Develop the metric hierarchies, dashboards, and reporting that turn supply decisions into shared understanding across the company
- Contribute analyses and recommendations to executive forums, and co‑author the supply narrative shared with the CTO and staff
Technologies
PythonSQLdata visualization toolscausal inference methods
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