Data Scientist, AI Compute & Impact

Anthropic; San Francisco (CA); Hybrid; USD 285,000 - 460,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching (optional)

Generous vacation and parental leave

Flexible working hours

Office in San Francisco

Job summary

Anthropic is seeking a data‑driven, technically adept professional to optimize compute allocation across a heterogeneous hardware fleet. You will build metrics and analytical frameworks to illuminate tradeoffs and partner with infrastructure teams to translate insights into production changes.

You will address causal‑inference challenges around rate limits, pricing, and routing, aiming to link actions to user outcomes and present findings to senior leadership for strategic decisions.

Qualifications

• Strong technical individual-contributor background in data science, analytics, or operations research.
• Fluent in causal inference and identifying effects, not just measuring them.
• Proficient in Python, SQL, and data visualization tools.
• Experience with production systems and collaborating with engineering teams.
• Alignment with Anthropic’s mission of building helpful, honest, and harmless AI.

Responsibilities

• Build and run testing frameworks to quantify how inputs affect compute allocation outcomes.
• Link compute allocation decisions to downstream user outcomes (retention, value, revenue).
• Collaborate with infrastructure, product, and research to instrument systems and ship changes.
• Develop metric hierarchies, dashboards, and reporting for supply decisions.
• Present analyses to executive forums and co-author the supply narrative with CTO.

Skills

Data science

Analytics

Operations research

Python

SQL

Data visualization

Production systems

Education

Bachelor's degree

Tools

LP/MILP

Queueing theory

RL-based control

Job description

Anthropic is seeking a data‑driven, technically adept professional to optimize compute allocation across a heterogeneous hardware fleet. You will build metrics and analytical frameworks to illuminate tradeoffs and partner with infrastructure teams to translate insights into production changes.

You will address causal‑inference challenges around rate limits, pricing, and routing, aiming to link actions to user outcomes and present findings to senior leadership for strategic decisions.