Applied Scientist II, Amazon Fulfillment Technology , Amazon Fulfillment Technologies (AFT)

The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Applied Scientist, with strong optimization and analytical skills, to develop production solutions for one of the most complex systems in the world: Amazon’s Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, pick assignment and scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network.

• Key job responsibilities
• As an Applied Scientist, you will work with other scientists, software engineers, product managers, and operations leaders to develop scientific solutions and analytics using a variety of tools and observe direct impact to process efficiency and associate experience in the fulfillment network. Key responsibilities include:

• * Develop an understanding and domain knowledge of operational processes, system architecture and functions, and business requirements
• * Deep dive into data and code to identify opportunities for continuous improvement and/or disruptive new approach
• * Develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and new challenges
• * Create prototypes and simulations for agile experimentation of devised solutions
• * Advocate technical solutions to business stakeholders, engineering teams, and senior leadership
• * Partner with engineers to integrate prototypes into production systems
• * Design experiment to test new or incremental solutions launched in production and build metrics to track performance

• A day in the life
• Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
• 1. Medical, Dental, and Vision Coverage
• 2. Maternity and Parental Leave Options
• 3. Paid Time Off (PTO)
• 4. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

• About the team
• Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.

The AFT Science team has expertise in operations research, optimization, scheduling, planning, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.

Basic qualifications

• - PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
• - 2+ years of building models for business application experience
• - Experience programming in Java, C++, Python or related language
• - Relevant industry or academic applied research experience in operations research, optimization, machine learning, statistics or an equivalent field.

Preferred qualifications

• - PhD with applied research experience and expertise in Operations Research, Optimization, Machine Learning, Statistics, or an equivalent field
• - Experience in large scale optimization and decomposition techniques, planning and scheduling problems
• - Experience in building machine learning models and developing algorithms for business applications
• - Experience in developing and deploying code for production systems
• - Experience with exploratory data analysis and experimental design

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually