Applied Scientist, Amazon Fulfillment Technologies (AFT)

The Amazon Fulfillment Technologies (AFT) Science team is looking for an innovative and experienced Applied Scientist, with strong machine learning and time series skills to develop forecasting models 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, order 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
- 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.
- Drive model development with a combination of econometrics, statistics, machine learning and analytical techniques to create scalable solutions for business problems.
- Research and develop new methodologies for demand forecasting, alarms, alerts and automation with advanced models and methods.
- Improve upon existing methodologies by adding new data sources and implementing model enhancements.
- Drive scalable and hands-off-the-wheel solutions.
- Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.
- Partner with engineers to integrate prototypes into production systems.
- Set high standards of coding and integrate successful models and algorithms in production systems.
- Use the best practices in science: data integrity, design, test, and implementation and documentation.
- Design experiment to test new or incremental solutions launched in production and build metrics to track performance.
- Contribute to Amazon's Intellectual Property through patents and internal and external publications.

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. - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 2+ years of building models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience applying theoretical models in an applied environment
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Strong technical skills and experience in Forecasting, Deep Learning, and Time series modeling or/and Causal Inference- 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 developing and deploying code for production systems
- Experience with exploratory data analysis and experimental design

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 $136,000/year in our lowest geographic market up to $223,400/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.