The Transportation Optimization Research team seeks experienced Applied and Research Scientists with strong analytical skills to join our team. We are focused on improving Amazon's customer experience and in saving hundreds of millions of dollars using cutting edge optimization, simulation, machine learning, and scalable distributed software.
We build systems that use real time, large scale optimization techniques to make operational, tactical and strategic decisions in the fulfillment space. We optimize how each customer order gets fulfilled striving to maximize customer experience, deliver fast and keep our fulfillment costs low. We also own network control algorithms that ensure that capacities are allocated optimally and we run strategic models that dynamically change the structure of our supply chain network by adding or removing fulfillment paths to increase our overall operational efficiency.
As a member of this team, the candidate will play an integral part in Amazon.com's Supply Chain Optimization Technologies by successfully partnering with various Operations, Product, and Finance teams to support new business initiatives. The candidate will also work closely with affiliated science teams to leverage the expertise of each individual to construct models, perform analyses, and derive relevant metrics.
This position requires superior analytical thinkers, able to approach large ambiguous problems and apply their technical and statistical knowledge to identify opportunities for further research. You should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.
• Interact with various software and business groups to develop an understanding of their business requirements and operational processes.
• Apply the acquired knowledge and business judgment to build decision-supporting and operational tools to improve the bottom line.
• Build quantitative mathematical models to represent a wide range of supply chain, transportation and logistics systems.
• Perform quantitative, economic, and numerical analysis of the performance of these systems under uncertainty using statistical and optimization tools such as R, Python and XPRESS to find both exact and heuristic solution strategies for optimization problems.
• Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements that can realize these improvements.
• Apply Mathematical optimization techniques, including Linear Programming, Integer Programming, Dynamic Programming, Network optimization algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software.
• Apply Machine Learning and regression techniques to tackle predictive modeling problems.
• Create software prototypes to verify and validate the devised solutions methodologies.
To help describe some of our challenges, we created a short video about Supply Chain Optimization at Amazon - http://bit.ly/amazon-scotBASIC QUALIFICATIONS
• PhD degree in operations research, statistics, applied math, computer science, engineering, or related technical/scientific field
• Strong fundamentals of statistics and probability, particularly their application in systems analysis and operations research.
• Fluency in at least one programming or scripting language (e.g. Python, Java, C, C++).
• Experience with SQL and Statistical Computing tools (e.g. R, SPSS).
• Strong problem solving and data analysis skills.
• Experience with fast prototyping
• Excellent written and verbal communication skills.
• 6+ years of related work experience.PREFERRED QUALIFICATIONS
• Experience with design, application, and optimization of complex logistics software management systems.
• Experience with control solutions like PID Controllers.
• Professional experience with inventory planning and supply chain management (forecasting, planning, optimization, and/or logistics).
• Experience working with data mining on large datasets ("big data").
• 10+ years of related work experience.