Research Scientist, GES NA Ops Engineering

Amazon•Bellevue, WA

6d•Onsite

About The Position

Amazon created one of the most sophisticated supply chains in the world. From the introduction of Amazon Prime, to the use of advanced technology for package delivery, Amazon consistently drives change from the front of the pack. Amazon is seeking a detail oriented Research Scientist to focus on simulation to assist with process improvement and facility design initiatives in our North American fulfillment network. Successful candidates will be natural self-starters who have the drive to design, model, and simulate new fulfillment center conception and design processes. The Research Scientist will be expected to deeply investigate complex problems and drive relentlessly towards innovative solutions. This role requires collaboration with cross-functional teams to develop and integrate advanced computer vision technologies that detect operational anomalies in real-time, improve equipment reliability, and enhance process efficiency. Key responsibilities include applying computer vision, data modeling, optimization techniques, and advanced analytics (e.g. statistical analysis, regression, DOE) to drive data-informed decisions on processes and designs, integrating new solutions into daily workflows to enable proactive interventions and reduce manual troubleshooting, and demonstrating strong technical expertise, problem-solving skills, and the ability to work effectively across the organization. The ideal candidate will have a track record of delivering impactful, technology-driven solutions through analytical rigor and creative thinking. This role requires a strong passion for customers, a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results. The ideal candidate will have experience in Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities in sourcing processes. Excellent business and communication skills are a must to develop and define key business questions and to build data sets. You should have demonstrated ability to think strategically and analytically about business, product, and technical challenges. You must be responsive, flexible, and able to succeed within an open collaborative environment. Amazon’s culture encourages innovation and expects to take a high-level of ownership in solving complex problems. Come help us make history!

Requirements

Master's degree or equivalent in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field
2+ years of building quantitative solutions as a scientist or science manager experience
Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
Expertise in at least one of the following areas: Discrete Event Simulation, Linear Programming, Natural Language Processing and Computer Vision.
2+ years strong coding skills in C++, Python or any other scripting languages

Nice To Haves

PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or PhD and 5+ years of industry or academic research experience
Experience communicating research findings and analysis in both written and spoken channels
Experience with theory and practice of design of experiments and statistical analysis of results
Experience with unstructured textual data
Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences

Responsibilities

Applying computer vision technologies to detect operational anomalies in real-time, the Research Scientist will be responsible for developing solutions that improve equipment reliability and process efficiency. These innovative capabilities will be integrated into daily workflows to enable proactive interventions and reduce manual troubleshooting, driving measurable improvements across the organization.
Design, develop, and simulate engineering solutions for complex material handling challenges considering human/equipment interactions for the North America fulfillment network
Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
Analyze historical data to identify trends and support decision making.
Provide requirements to develop analytic capabilities, platforms, and pipelines.
Design, size, and analyze field experiments at scale.
Build decision-making models and propose solution for the business problem you defined. This may include delivery of algorithms to be used in production systems.
Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
Utilize code (python or another object oriented language) for data analyzing and modeling algorithm
Develop, document and update simulation standards, including standard results reports
Create basic to highly advanced models and run "what-if" scenarios to help drive to optimal solutions
Analyze historical data to identify trends and support decision making.
Apply statistical or machine learning knowledge to specific business problems and data.
Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
Provide requirements to develop analytic capabilities, platforms, and pipeline
In-Office 5 Days per week (RTO)
Ability to travel up to 10%