At Adaptive Transportation Optimization Service (ATROPS), we solve the transportation problems associated with moving an object from point A to point B in the best way for the customer, while minimizing transportation capacity risks, stress on our fulfillment operations, carbon impact, and cost.
In this position, you will be at the forefront of the science associated with the most innovative logistics operation in the world. Your opinions and skills will change the world of commerce. You will be surrounded by experts who are passionate about their ideas, and loved for your passion about yours.
Key job responsibilities
- Build and share subject matter expertise around mathematical research happening around Amazon Fulfillment Optimization
- Drive research, collaborate with peers, and solve optimization problems through mathematical models
- Bring your concepts to life through detailed proposals, experimentation, data collection, and measured success
- Solve the biggest puzzle of all: explaining what is going on to internal customers and business partners
- Mentor junior engineers and scientists
- Partner with engineering teams who will integrate your models and solutions with systems, services, and integration gateways
- Make your work known and contribute to the field by producing publications
About the team
The Flow Planner and Optimization team handles mathematics associated with building the optimal shipment routes, reducing strain on the transportation network, and minimizing churn throughout the fulfillment lifecycle. These solutions are driven by ML models and exposed through a robust set of APIs and UI tools. Every fulfillment system is our customer, but our end customer is the Amazon shopper. Delighting the shopper is our primary focus, and our central strategy.
- Ph.D./M.S. in Computer Science, Operational Research, Statistics or a related quantitative field
- 2+ years of hands-on experience in modeling and analysis
- 2+ years hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
- Proficiency in model development, model validation and model implementation for applications
- Strength in distilling problem definitions, models, and constraints from complex business problems and requirements
- Proven peer-reviewed scientific contributions in publications and/or conferences
- Ability to convey mathematical results to non-science stakeholders
- Proven experience owning projects in an leading capacity, creating and defending vision and bringing concepts to life
- Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
- Proven track record in technically leading and mentoring scientists
- Ability to convey rigorous mathematical concepts and considerations to non-experts
- Ability to work on a diverse team or with a diverse range of coworkers
- Significant contributions to the scientific field, recognized in publications and congress of peers
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.