Senior Applied Scientist , ECOptimization Science

AWS Elastic Compute Cloud (EC2) Capacity Org is seeking an experienced applied optimization expert to join the Optimization Science Team. The role involves designing, implementing, and scaling decision‑making algorithms that manage EC2’s virtual and physical capacity, aligning supply and demand across horizons from five minutes to thirteen years. The team owns the top‑level customer satisfaction metric capacity availability and the forecasting & decision‑making systems that drive critical capex investments in AWS data centers.

• Design, implement, and scale optimization algorithms to manage EC2 capacity and meet customer demand.
• Apply continuous and discrete mathematical optimization, robust or stochastic methods, and ML/GenAI techniques to large‑scale problems.
• Analyze large volumes of data, develop prescriptive optimization models, and validate solutions through simulations and production A/B tests.
• Review approaches from other scientists and engineers for business relevance, technical validity, and computational performance.
• Mentor and lead junior scientists, guiding them through the end‑to‑end delivery cycle from data analysis to production.
• Communicate results to business stakeholders and software development teams, producing technical and business documents that influence engineering investments.
• Collaborate with scientists, software engineers, and product managers to develop novel, data‑driven approaches that improve cloud compute offerings.

Basic Qualifications

• PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or a master’s degree with 4+ years of building machine learning models or developing business‑application algorithms.
• Knowledge of optimization mathematics such as linear programming and nonlinear optimization.
• Experience with databases (SQL, MySQL) and ETL for large data sets.
• In‑depth expertise in continuous and discrete optimization methods and associated tools (CPLEX, Gurobi, XPRESS).
• Experience prototyping and developing software in languages such as C++, Java, Python, or Julia using mathematical solver interfaces.
• Strong written communication skills for documenting models, analyses, and business cases.

Preferred Qualifications

• Knowledge of quantitative data analysis and statistics.
• Experience applying machine learning to optimization problems.
• Experience with decision‑making under uncertainty, such as robust or stochastic optimization.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

• Competitive base salary range: $167,100 – $226,100 annually (Seattle, WA).
• Sign‑on payments and restricted stock units (RSUs).
• Comprehensive health, dental, vision, and life insurance coverage.
• 401(k) matching, paid time off, parental leave, and other benefits.