Applied Scientist, SCOT-Inbound Systems

Amazon; Bellevue (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon's IRR Science team in SCOT-Inbound Systems seeks a highly qualified Applied Scientist to design and implement optimization and ML solutions for inventory routing, replenishment, and network design. You will prototype, test, and deploy models at Amazon scale, collaborating with software engineers and product teams.

You have a PhD in a quantitative field, hands-on experience with Java/Python, and a passion for translating theory into production-ready algorithms and software.

Qualifications

• PhD in operations research, applied mathematics, theoretical computer science, or equivalent.
• Experience programming in Java, C++, or C# with OO design.
• Experience applying theoretical models in an applied environment.
• Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
• Experience building machine learning models or developing algorithms for business applications.
• Experience with CPLEX, GUROBI, or XPRESS.

Responsibilities

• Design and develop advanced mathematical optimization and machine learning solutions for inventory optimization, distribution optimization, network design, and control theory.
• Develop online and offline control techniques and heuristic methods for decision support tools.
• Prototype, simulate, and experiment with models using Java and Python; participate in deployment.
• Write production-level Java/Python code and provide on-call support.
• Create and maintain technical documentation and science designs.
• Present findings to scientists, product teams, and software engineers; stakeholders.
• Lead project plans from a scientific perspective, managing features, risks, milestones, and launches.
• Mentor other scientists and influence the team's long-term roadmap.

Skills

Java

C++

C#

Object-oriented design

Numerical optimization

Data mining

Parallel computing

Distributed computing

High-performance computing

Machine learning models

Education

PhD in operations research / applied mathematics / theoretical computer science

Tools

CPLEX

Gurobi

Xpress

Job description

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

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

Company - Amazon.com Services LLC

Job ID: A10552747