Amazon opened its virtual doors in 1995 and strives to be the world's most customer-centric company, where customers can find and discover anything they might want to buy online.
The Amazon Logistics team is offering positions to creative big thinkers who are passionate about using data to direct decision making and solve complex and large-scale challenges. We are looking for individuals with a strong interest in improving one of the world's most complex logistic systems. As part of the Amazon Logistics team, we design and build systems that support planning decisions, measure and manage the last mile transportation, real estate investments, and resource planning.
As an Operations Research Scientist, you will use your experience to develop new solutions to improve the performance of Amazon Logistics. Working closely with groups such as program managers, operation, business analysts, data scientists and research scientists, you will support various business initiatives and use your experience in modeling, statistics, simulation and optimization to design models of new policies, simulate and optimize their performance, and evaluate their benefits and impacts to cost, reliability, and speed of our outbound transportation network. You will present your findings to your peers and senior management, and work with program managers to integrate the findings into our product plans.
This position requires superior analytic thinkers, who are able to quickly 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 and be able to measure and estimate risks.
We'll expect you to go the extra mile, but we'll also make sure you're well rewarded. As well as a competitive salary and stock units, we offer a whole host of other benefits, including an employee discount.
There are other, more intangible rewards too. Like our commitment to your development, a refreshing lack of hierarchy, the chance to work with some of the brightest minds in the industry, plenty of team spirit and an informal atmosphere - suits and ties are few and far between.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief.
• Masters in Operations Research, Statistics, Applied Mathematics, Computer Science or a related field.
• Experience designing and implementing optimization models in for inventory, networks and other characteristics of supply-chain systems (e.g., staff scheduling, vehicle routing, and facility location).
• Good communication skills with both technical and business people. Ability to speak at a level appropriate for the audience. Experience applying these skills in both academic teaching environment and a business setting is a plus.
• A working knowledge of optimization methods accompanied by associated expertise in the use of tools and the latest technology (e.g. CPLEX, Gurobi, XPRESS).
• The ability to implement models and tools through the use of high-level modeling languages like Python.
• Familiarity with SQL and experience with very large-scale data. The ability to manipulate data by writing scripts is a plus.
• Ph.D. in Operations Research, Statistics, Applied Mathematics, Computer Science or a related field and at least 3 years work experience.
• Statistical analysis, machine learning and data-modeling in a database environment a plus.
• Experience writing supply chain and inventory optimization models and applying optimization models in for strategic and tactical business decisions.
• Experience applying forecasting and data mining techniques in an industrial setting.
• Demonstrated experience designing/building forecasting systems and business metrics.