Founding Data Scientist, Capacity & Pricing Optimization

Fireworks • San Mateo, CA

1d • $250,000 - $300,000

About The Position

Fireworks is hiring its first Data Scientist to build and own quantitative models for pricing, packaging, and capacity allocation. The role focuses on effectively deploying GPUs to meet customer demand, optimizing capacity, and balancing supply with demand. The ideal candidate combines operations research and economics expertise with the ability to model markets, develop dynamic pricing models, and design experiments and causal studies. This is a hands-on role involving production-quality code, models that drive real decisions, and ownership of priorities as well as execution.

The work spans supply and demand modeling, pricing optimization, and GPU mix optimization. The Data Scientist will develop fill-rate and capacity-buffer models; create pricing policies and experiments to improve utilization and price-yield; and optimize model-to-hardware matching and capacity sourcing decisions across GPU generations, vendors, clouds, regions, commitment types, and terms.

Requirements

• Master’s degree in Operations Research, Economics, Industrial Engineering, Statistics, or a related quantitative field.
• At least 7 years of hands-on experience in pricing, revenue management, or optimization.
• Strong grounding in at least two of the following: stochastic optimization, revenue management and pricing, causal inference and experimental design, or combinatorial optimization.
• Track record of delivering production-quality models that drive direct business impact.
• Strong coding skills and experience with optimization tooling and methodologies.
• Ability to communicate tradeoffs and uncertainty clearly to engineers and executives.

Nice To Haves

• PhD.
• Experience on capacity planning, forecasting, or pricing science teams at a cloud computing provider or marketplace business.
• Familiarity with GPU infrastructure and LLM inference economics, including throughput, batching, utilization, and cost per token.
• Experience as the first quantitative hire in a new function, building models and data pipelines from scratch.

Responsibilities

• Build fill-rate models for serverless inference that balance utilization against performance and latency targets.
• Model how traffic is shared and multiplexed across models and customers to set safe capacity buffers.
• Design pricing for low-utilization capacity, including spot and preemptible offerings, off-peak and overnight windows, and sub-scale capacity pools.
• Develop pricing policies to optimize capacity utilization and price-yield.
• Design and execute experiments and causal studies to estimate elasticity across customer segments, models, and products.
• Optimize model-hardware matching across GPU generations, vendors, clouds, and regions, accounting for workload fit, substitution, and lead times.
• Optimize capacity across commitment types and terms, quantifying tradeoffs among cost, flexibility, and utilization risk to guide capacity sourcing.
• Write production-quality code and deliver models that drive business decisions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior