- Bellevue, WA
Does the thought of improving one of the world's most complex logistic systems inspire you? Are you fascinated by the interactions between operations and strategy? Do you want to be part of an organization that is on the leading edge of operations involving sortation, distribution, and logistics as Amazon delivers world class service to our customers? The Amazon NASC Material Flow Team (MFO) seeks to optimize site configurations, automate operational decisions, and develop operational models to maximize capacity and reduce variable cost at scale. We are looking for a proven technical leader with extensive model, simulation, scripting, and communication skills to join the effort in evolving the network we have today into the network we need tomorrow. Amazon's extensive logistics system comprises thousands of fixed infrastructure nodes with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements truly unparalleled. This magnificent challenge is a terrific opportunity to understand, model, simulate, optimize, and reshape one of the world's most complex systems.
Your main focus will be on developing model-based , simulation, and/or tools to identify and evaluate opportunities to improve customer experience, network speed, cost, and the efficiency of capital investment. You will quantify the improvements resulting from the application of these tools and you will evaluate the trade-offs between potentially competing objectives.
The ideal candidate will have good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders from operations, finance, IT, and business leadership.
• Ph.D. in Operations Research, Industrial Engineering, Computer Science, Chemical Engineering, Engineering, Statistics, Applied Mathematics, or related field OR Masters Degree plus 4 years of quantitative experience
• Experience developing models and algorithmic solutions tailored to particular business problems
• Experience writing scripts to manipulate data and developing software in traditional programming languages (e.g., C/C++, Java, Python).
• Excellent communication skills with both technical and non-technical audiences.
• Familiarity with simulation modeling using FlexSim, ARENA, Simio, SimPy or a similar software
• Some travel maybe required
• Ph.D. in Operations Research, Industrial Engineering, Computer Science, Chemical Engineering, Engineering, Statistics, Applied Mathematics, or related field
• Relevant work experience with demonstrated impact in decision support applications (e.g., scheduling, vehicle routing, facility location, assignment problems, revenue management)
• Practical experience developing decision support tools based on technology (e.g., LP, MIP, NLP, etc...)
• Practical experience with simulation modeling
• Familiarity with processes and under uncertainty
• Familiarity with and time series analysis
• Familiarity with techniques and technologies
• Familiarity with data visualization (e.g. R, Tableau, GIS software)
• Ability to work on a diverse team or with a diverse range of coworkers
Amazon is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us We believe passionately that employing a diverse workforce is central to our success and we make recruiting decisions based on your experience and skills. We welcome applications from all members of society irrespective of age, gender, disability, sexual orientation, race, religion or belief.
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