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Description

Amazon is building the largest Electric Vehicle (EV) delivery fleet and charging network in the world as part of our Climate Pledge. The Global Fleet and Products (GFP) Electrification & Infrastructure (E&I) team is responsible for accelerating Amazon's electrification and facilitating the successful transition of our delivery fleet to achieve net zero-emissions in support of The Climate Pledge. This role sits on the Planning and Data Systems team within GFP E&I. Our mission is to install the right EV chargers at the right place, at the right time to enable the most cost optimized solution to delivery electrification. Our team builds the disciplinary science and data tools necessary to support electrification and guide investment decisions for GFP.

We are seeking a talented and innovative research scientist with a passion for building enterprise science solutions and infrastructure components that are highly scalable, extensible, and robust. In this role, you will help us optimize our infrastructure planning, trading costs between different operational levers, technologies, and business needs. You will also help model the impact new innovations in charging, planning, operations will have on our business. This individual needs to partner with engineering, analytics, operations, and product teams across three large organizations.

Key job responsibilities

You will immerse yourself at the intersection of operations, hardware, software, and simulation systems to develop long term electrification strategies across Last Mile and Middle Mile businesses. You’ll need to be familiar with AWS services (Glue, EMR, S3, Lambda, Redshift, QuickSight, SageMaker, etc.), operations research, optimization models, and be able to drive best practices with continuous improvement and development.

Basic Qualifications

- 5+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience

- PhD, or Master's degree and 5+ years of quantitative field research experience

- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.

- Experience communicating qualitative research methods and findings to non-qualitative researchers

- Deep knowledge of Operations Research, such as mixed-integer linear programming, stochastic programming, simulation. And experience with mathematical programming software packages like Xpress, CPLEX, or Gurobi.

Preferred Qualifications

- Experience converting research studies into tangible real-world changes

- Experience with discrete and continuous optimization methodologies and algorithms

- Knowledge of R or Python

- Experience applying OR tools to ambiguous business problems, particularly around EV chargers

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.