Research Scientist II, Modeling & Optimization

Key Skills

Ruby on Rails, Java Programming, Python Programming, C++, C Programming, SQL, Machine learning techniques, Perl Programming, Data Visualization, Data Modeling, Natural Language Processing (NLP), Tableau, Algorithms, ggplot, Large scale data processing

Job Description

Does the thought of improving one of the world’s most complex logistic systems inspire you? Are you a creative thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? Are you fascinated by the interactions between operations and strategy? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! Amazon's Modeling and Optimization team (MOP) is looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the network we have today into the network we need for tomorrow.

Key job responsibilities

Amazon’s extensive logistics system is comprised of thousands of fixed infrastructure nodes, with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements unparalleled. This magnificent challenge is a great opportunity to analyze Amazon’s transportation network and generate actionable recommendations using optimization and simulation. Come build with us!

A day in the life

In this role, your main focus will be to perform analysis, synthesize information, identify business opportunities, provide project direction, and communicate business and technical requirements within the team and across stakeholder groups. You consider the needs of day-to-day operations and insist on the standards required to build the network of tomorrow. You will learn current processes, build metrics, educate diverse stakeholder groups, assist science groups in initial solution design, and audit all model implementation. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made.

About the team

The ideal candidate will demonstrate a deep understanding of quantitative decision-making process with meaningful key performance indicators and is passionate about providing insights that drive larger initiatives. They are excited to be part of, and learn from, a large science community and are ready to dig into the details to find insights that direct decisions. The successful candidate will have good communication skills and an ability to speak at a level appropriate for the audience, and will deliver business value in close partnership with many stakeholders from operations, finance, IT, research, and business leadership.

BASIC QUALIFICATIONS

• Ph.D in Operation Research, Transportation Engineering, Industrial Engineering, Statistics, Applied Mathematics, Computer Science or a related field
• Experience implementing algorithms, tailored to particular business needs and tested on large data sets.
• Experience developing optimization models for business decisions
• Experience writing scripts (Perl, Python, Ruby) to manipulate data and developing software in traditional programming languages (e.g., C/C++, Java).

PREFERRED QUALIFICATIONS

• Ph.D and at least 2-3 years work experience working as a member of an analysis team in the transportation or closely related field.
• Practical experience developing large-scale decision support tools based on optimization technology (e.g., LP, MIP, NLP, etc...) for planning and execution support (e.g., staff scheduling, vehicle routing, facility location)
• Familiarity with data visualization (e.g. R, ggplot, ggobi, Tableau)
• Familiarity with machine learning techniques and technologies
• Familiarity with large-scale simulation modeling

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