Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team

• Our goals are to increase reliable access to supply, improve supply chain-driven vendor experience, and reduce end-to-end supply chain costs, all in service of maximizing Long-Term Free Cash Flow (LTFCF) for Amazon.
• Key job responsibilities
• Set the scientific strategic vision for the team. Lead problem decomposition and roadmap development.
• Identify and frame research challenges in ambiguous problem areas; invent novel methodologies to address them. Distinguish between problems requiring novel solutions versus those addressable with existing approaches.
• Exercise sound judgment to prioritize between short-term vs. long-term and business vs. technology needs.
• Set an example with exemplary scientific analyses; maintainable, well-tested code; and simple, effective solutions.
• Drive the design of scientifically-complex software solutions, personally writing critical-path code that embodies scientific novelty. Deploy novel models into production with a track record of impactful delivery.
• Develop reusable science components that resolve architecture deficiencies; set standards and drive adoption of state-of-the-art techniques.
• Influence team business and engineering strategies. - Communicate effectively with stakeholders to drive alignment and build consensus.
• Foster collaborations between scientists across Amazon researching similar problems. Proactively resolve endemic issues where the team's technologies bottleneck other teams.
• Actively engage in the development of others, both within and outside the team.
• Participate in the science hiring process and engage with the broader scientific community through publications, presentations, and patents.
• PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or Master's degree and 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
• Knowledge of supply chain management concepts - forecasting, planning, sourcing, optimization and logistics or equivalent
• Experience building and deploying machine learning or optimization models for business applications at scale
• Proficiency in Python with experience developing production-quality scientific software
• Technical depth in one or more of: mathematical optimization, causal inference, sequential decision-making (RL/MDP), or stochastic modeling
• Publication record in operations research, machine learning, or a related quantitative field
• Experience with optimization solvers (e.g., Gurobi, OR-Tools) or reinforcement learning frameworks (e.g., RLlib, Stable Baselines)
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
• Experience designing and analyzing experiments in operational or supply chain settings
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually

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