Sr. Simulation Scientist, Amazon Logistics

Role Overview Are you inspired by invention? Do you like the idea of seeing how your work impacts the bigger picture? If you answered yes, you’ll fit right in here at Amazon Last Mile Simulations and Analytics Engineering team. WW AMZL Simulations and Analytics Engineering team is looking to build out our Simulation team to drive innovation across our Last Mile network. We start with the customer and work backwards in everything we do. If you’re interested in joining a rapidly growing team working to build a unique, solutions advisory group with a relentless focus on the customer, you’ve come to the right place. This is a blue‑sky role that gives you a chance to roll up your sleeves and dive into big data sets in order to build discrete event 3D simulations using tools like FlexSim, AnyLogic, Emulate 3D, etc., and experimentation systems at scale, build optimization algorithms, and leverage advanced technologies across Amazon. This is an opportunity to think big about how to solve a challenging problem for the customers. As a Sr. Simulation Scientist, you are expected to deep dive into complex problems and drive relentlessly towards innovative solutions working with cross‑functional teams. Be comfortable interfacing and influencing various functional teams and individuals at all levels of the organization in order to be successful. Lead strategic modelling and simulation projects related to drive process design decisions. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. You will apply advanced designs and methodologies for complex use cases across Last Mile network to drive innovation. In addition, you will contribute to the end‑state vision for simulation and experimentation of future delivery stations at Amazon. Key Responsibilities Lead the design, implementation, and delivery of the simulation data science solutions to perform system‑of‑systems discrete event simulations for significantly complex operational processes that have a long‑term impact on a product, business, or function using FlexSim, Demo 3D, AnyLogic or other DES software packages. Lead strategic modeling and simulation research projects to drive process design decisions. Be an exemplary practitioner in simulation science discipline to establish best practices and simplify problems to develop discrete event simulations faster with higher standards. Identify and tackle intrinsically hard process flow simulation problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact). Deliver artifacts that set the standard in the organization for excellence, from process flow control algorithm design to validation to implementations to technical documents using simulations. Be a pragmatic problem solver by applying judgment and simulation experience to balance cross‑organization trade‑offs between competing interests and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors for multiple simulation projects. Provide simulation data and measurements that influence the business strategy of an organization. Write effective white papers and artifacts while documenting your approach, simulation outcomes, recommendations, and arguments. Lead and actively participate in reviews of simulation research science solutions. Bring clarity to complexity, probe assumptions, illuminate pitfalls, and foster shared understanding within the simulation data science discipline. Mentor and educate the larger simulation data science community on trends, technologies, and best practices. Use advanced statistical/simulation tools and develop codes (Python or another object‑oriented language) for data analysis, simulation, and developing modeling algorithms. Lead and coordinate simulation efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow control logic, process design, and site layout. Deliver results according to project schedules and quality standards. Basic Qualifications 5+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products. 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. Preferred Qualifications Experience with discrete and continuous optimization methodologies and algorithms. Experience converting research studies into tangible real‑world changes. Industry experience leveraging tools such as Discrete Event simulations FlexSim, AnyLogic, Emulate 3D to solve complex business problems. 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, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. The base salary range for this position is 159,200.00 – 215,300.00 USD annually. Amazon also offers sign‑on payments, restricted stock units, and comprehensive benefits including health insurance, 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. #J-18808-Ljbffr