Founding Data Scientist, Capacity & Pricing Optimization

Highlights

• Build quantitative models driving GPU pricing, packaging, and capacity allocation.
• Design dynamic pricing for spot, preemptible, and off-peak inference capacity.
• Optimize GPU mix across generations, vendors, clouds, and regions.

Ideal candidate

An ownership-driven quantitative thinker who thrives at the intersection of operations research and economics and loves shipping models that shape real pricing and capacity decisions.

Requirements

• Master's degree in Operations Research, Economics, Industrial Engineering, Statistics or related field with 7+ years in pricing, revenue management, or optimization
• Strong grounding in at least two of stochastic optimization, revenue management and pricing, causal inference and experimental design, or combinatorial optimization
• Track record of delivering production-quality models driving direct business impact
• Strong coding skills and experience with optimization tooling and methodologies
• Ability to communicate tradeoffs and uncertainty clearly to engineers and executives
• Experience on capacity planning, forecasting, or pricing science teams at a cloud provider or marketplace business
• Familiarity with GPU infrastructure and LLM inference economics including throughput, batching, utilization and cost per token
• Experience as first quantitative hire building models and data pipelines from scratch