Data Scientist, Middle Mile Transportation (NEST)

- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 2+ years of data scientist experience
- Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
- Experience applying theoretical models in an applied environment
- Hands-on experience with machine learning, time series modeling, optimization techniques/math programming, simulation methods (discrete event, agent-based)
- Experience in communicating technically, at a level appropriate for the audience
- Experience using AWS tools such as SageMaker, S3, Lambda and Dynamo DB
- Experience in building optimization models and implementing them using commercial solvers (e.g. CPLEX, Gurobi, XPRESS etc.)
- Experience in building simulation models using commercial software (ARENA, AnyLogic, Flexsim etc.)

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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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.
Have you ever placed an order on Amazon and wondered how it got to you- or how it got to you so fast? Do you get excited thinking about the data and technology that power complex transportation networks and would like to build some of the models enabling their growth? Then, come join Network Engineering, Scheduling and Technology (NEST) Science team within the Amazon Transportation Services and help us innovate the way packages flow to our customers.

We are looking for a Data Scientist specializing in the development of simulation and optimization algorithms applied to network planning and transportation labor management. This includes the development, enhancements and implementation of predictive and prescriptive components within the network, and creating analytical tools to improve network planning solutions. The successful candidate will have strong modeling skills and is comfortable owning their own data and working from concept through to execution, including the software implementation in a production environment in collaboration with software development teams.

A qualified candidate is a problem-solver and should have demonstrated ability to build methodology and tools that are statistically grounded. The ideal candidate will have curiosity towards developing self-service and/or fully automated optimization and machine learning applications.



Key job responsibilities
- Design and contribute to the components of automated prediction and optimization applications dictating key planning outputs in transportation planning and labor management
- Developing code (Python, R, Scala, etc.) for analyzing data and building statistical models to solve specific business problems; improving upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
- Building science-based applications leveraging discrete event, agent based simulation methods, applications (AnyLogic, Arena, etc.) OR optimization methods, solvers (Gurobi, Xpress, CPLEX, AMPL, etc.)
- Manipulating/mining data from databases (Redshift, SQL Server, S3)
- Collaborating with other scientists, product managers and engineering teams to design and implement software solutions for problems within the Amazon Transportation network
- Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations

About the team
The Network Engineering, Scheduling, and Technology (NEST) Science Team prototype, build, and productionize mathematical models that reduce transportation cost and improve customer experience in Amazon's Middle Mile network. Equipped with techniques from Operations Research, Machine Learning and Simulation, these models are used to govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine the transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with technical Product Managers that come from diverse backgrounds.