At Amazon, we are constantly inventing and re-inventing to be the most associate-centric company in the world. To get there, we need exceptionally talented, bright, and driven people. Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers.
The GSF (Global Specialty Fulfillment) organization leads the innovation of Amazon’s ultra-fast fulfillment initiatives. Our key vision is to transform the online experience. We’re growing in scale and volume, by orders of magnitude. We are a team of passionate tech builders who work endlessly to make life better for our associates through amazing, thoughtful, and creative new scheduling experiences. To succeed, we need senior technical leaders to forge a path into the future by building innovative, maintainable, and scalable systems.
The ideal candidate will be responsible for quantitative data analysis, building models and prototypes for supply chain systems, and developing state-of-the-art optimization algorithms to scale. This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping/simulation, to implementation by working closely with colleagues in engineering, product management, operations, retail and finance.
As a member of the scientist team, you will play an integral part on our Supply Chain team with the following technical and leadership responsibilities: · Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements · Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization · Develop scalable mathematical models to derive optimal or near-optimal solutions to existing and new supply chain challenges · Create prototypes and simulations to test devised solutions · Advocate technical solutions to business stakeholders, engineering teams, as well as executive-level decision makers · Work closely with engineers to integrate prototypes into production system · Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features · Mentor team members for their career development and growth · Present business cases and document models, analyses, and their results in order to influence important decisions
· Ph.D. in Operations Research, Operations Management, Engineering, Computer Science, Applied Mathematics, or a related quantitative field · 2+ years of relevant industrial research experience in supply chain management, inventory management, operations management, simulation or a closely related field · 2+ years hands-on experience in a high level programming language (Python, Perl, Scala, Java, C#, C++ or other similar language) · Ability to distill problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives · Ability to quantify improvement in business areas resulting from optimization techniques through use of business analytics and/or statistical modeling · Demonstrated use of modeling and mathematical optimization techniques tailored to meet real life problems through a record of achievements in industrial and/or academic environments · Excellent written and verbal communication skills with technical and business teams; ability to speak at a level appropriate for the audience. The ideal candidate can present business cases and document the models and analysis and present the results in order to influence important decisions
· Hands-on experience in building end-to-end mathematical models and prototyping · Deep expertise in stochastic and deterministic optimization techniques and simulation · Experience in inventory optimization · Experience in common predictive analytic methods · Expert in one or proficient in more than one major programming language (Mosel, AMPL, Python, C/C++/Java, SSJ, Matlab, Arena, etc.) · A working knowledge of linear and non-linear optimization methods accompanied by expertise in the use of OR tools (e.g. CPLEX, Gurobi, XPRESS). · Expertise in prototyping with applications of efficient large-scale data analysis in a complicated system · Experience and/or academic research in area of online retail and competition with brick and mortar stores; mechanism design and coordination/contracting within supply chains; or Pricing and Revenue Management