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

Description

Amazon is looking for an Applied Scientist to help build the next generation of sourcing and vendor experience systems. The Optimal Sourcing Systems (OSS) owns the optimization of inventory sourcing and the orchestration of inbound flows from vendors worldwide. We source inventory from thousands of vendors for millions of products globally while orchestrating the inbound flow for billions of units. 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.

Basic Qualifications

• 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

Preferred Qualifications

• 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

About the role

Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including optimization, causal inference, and machine learning/deep learning.

Skills

• Mathematical optimization

• Causal inference

• Sequential decision-making (RL/MDP)

• Stochastic modeling

Benefits

Amazon offers a comprehensive benefits package including health insurance, retirement savings plans, and paid time off.

Pay

The salary range for this position is $120,000 - $170,000 annually, and the actual offer may vary based on factors such as level of experience, skills, and geographic location.

Schedule

This role is full-time.

Contact

If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations.