Data Scientist, Capacity Efficiency

Anthropic Anthropic · AI Frontier · Data Science & Analytics

This role focuses on optimizing and forecasting computing resource needs for AI research and product development. It involves analyzing infrastructure utilization data, partnering with engineering and finance to optimize capacity allocation, and developing models for future capacity requirements. The goal is to ensure efficient, scalable, and cost-effective infrastructure to support AI deployment.

What you'd actually do

  1. Analyze infrastructure and utilization data to define key metrics, understand trends, set team goals, provide actionable insights and identify optimization opportunities.
  2. Partner with stakeholders across engineering, research, product, operations and finance to improve predictability of capacity utilization and optimize the allocation of capacity across different users and products.
  3. Develop models to forecast future capacity needs based on business growth projections and product roadmaps.
  4. Identify and size opportunities to optimize infrastructure costs and performance, influencing the roadmap through your insights and recommendations.
  5. Build a data-driven culture within the infrastructure team by establishing foundational data best practices and making data more accessible.

Skills

Required

  • Python
  • SQL
  • data visualization tools
  • cloud based billing systems
  • efficiency optimization
  • infrastructure problems
  • capacity/compute

Nice to have

  • turning open questions and data into concise and insightful analysis
  • written communication and presentation skills

What the JD emphasized

  • capacity efficiency
  • scale our computing resources
  • infrastructure is efficient, scalable
  • capacity utilization
  • optimize infrastructure costs and performance
  • capacity/compute

Other signals

  • optimize infrastructure costs and performance
  • forecast future capacity needs
  • manage and scale computing resources