From Amazon's posting. “We” and “our” refer to the employer.
As part of IRR (Inventory Routing and Replenishment) organization within SCOT-Inbound systems, Applied Scientists own algorithms powering inventory routing, replenishment, and modeling / simulation of Amazon's fulfillment network utilizing optimization and machine learning toolsets. We are looking for a talented applied scientist with a passion for designing and implementing efficient and elegant scientific solutions for Amazon-scale supply chain problems.
Key job responsibilities
Design and develop advanced mathematical optimization and machine learning solutions in the domains of inventory optimization, distribution optimization, network design, and control theory.
Use methods in learned and model-based online and offline control techniques and algorithms to design efficient exact or heuristic solution methodologies to be used by in-house decision support tools and software.
Research, prototype, simulate, and experiment with these models using programming languages such as Java and Python; participate in the production level deployment.
Closely work with software engineering teams and write well-tested production Java/Python code for science modules within engineering-managed services. Provide time-sensitive on-call support and high-severity issue support when bugs are identified in production code. Improve code quality of legacy scientific production code.
Create, enhance, and maintain technical documentation and science designs.
Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders.
Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans.
Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists.
A day in the life
Engage with customers to understand their problems.
Collaborate with product partners and peers to design and deliver algorithmic solutions to these problems.
Implement these solutions in java within engineering systems through close collaboration with engineering partners achieving high code quality.
Deploy and measure impact of implementations.
Support customers and stakeholders whenever deep-dives and enhancements are needed as they relate to scientific products the team owns.
Contribute to product roadmap through new innovations on behalf of customers.
Publish work in internal and external scientific community.
About the team
IRR Science team under SCOT Inbound Systems is comprised of applied scientists with strong optimization & ML science depth. Given the scale of problems we solve for our customers and mission-critical nature of our solutions, systems thinking driven approach, with attention to algorithmic complexity, solution quality, simplicity, and extensibility are of critical importance. We collaborate with engineering teams closely and deliver clean code following software design patterns.
We build solutions that must consistently improve customer experience with maximum transparency and explainability of decisions made by such solutions. We strive for every member of the team to be knowledgeable about every product that the team owns to enable meaningful collaboration within the team. We seek to publish our work at internal and external scientific communities when they produce novel solutions.
Basic Qualifications
PhD in operations research, applied mathematics, theoretical computer science, or equivalent
Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
Experience applying theoretical models in an applied environment
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience building machine learning models or developing algorithms for business application
Experience with advanced use of 3P mathematical optimization software such as cplex/gurobi/xpress
Preferred Qualifications
Have publications at top-tier peer-reviewed conferences or journals
2+ years of building machine learning models or developing algorithms for business application experience
Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
Experience in designing experiments and statistical analysis of results
Equal Opportunity
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
About this listing
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
