About the job
Are you interested in working with top talents in Optimization, Operations Research and Supply Chain to help Amazon to efficiently match our Devices with worldwide customers? We have challenging problems and need your innovative solutions to make tremendous financial impacts! The Amazon Demand Science Optimization organization is looking for an Applied Scientist with background in Operations Research, Optimization, Supply Chain, Simulation, and Gen AI to support science efforts to integrate across inventory management functionalities. Our team is responsible for science models (both deterministic and stochastic) that power world-wide inventory allocation, promotion optimization for Amazon Devices business that includes Echo, Kindle, Fire Tablets, Amazon TVs, Amazon Fire TV sticks, Ring, and other smart home devices. We formulate and solve challenging large-scale financially-based optimization problems which ingest demand forecasts and produce optimal price promotion strategies, procurement, production, distribution, and inventory management plans. In addition, we also work closely with the demand forecasting, material procurement, production planning, finance, and logistics teams to co-optimize the inventory management and supply chain for Amazon Devices given operational constraints.
Responsibilities
Design and develop advanced mathematical, simulation, and optimization models and apply them to define strategic and tactical needs and drive appropriate business and technical solutions in the areas of inventory management and distribution, network flow, supply chain optimization, and demand planning
Apply mathematical optimization techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software
Research, prototype and experiment with these models by using modeling languages such as Python; participate in the production level deployment
Create, enhance, and maintain technical documentation, and present to other Scientists, Product, and Engineering teams
Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans
Influence the organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists
Qualifications
Minimum
PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
3+ years of building models for business application experience
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred
Experience in optimization mathematics such as linear programming and nonlinear optimization
PhD in math/statistics/engineering or other equivalent quantitative discipline, or a Associate's degree or above and experience applying optimization models in for business decision support or in optimized supervisory control
Experience in technical support, or experience with training and deploying machine learning systems to solve large-scale optimizations
Experience developing, deploying and managing AI products at scale
Experience in building optimization models and implementing them on OR tools (e.g. CPLEX, Gurobi, XPRESS)