Description

The Planning and Execution team (PLEX) is seeking a Research Scientist to build & improve mathematical optimization techniques and algorithms to support planning and execution activities throughout North America. PLEX is comprised of high-powered dynamic teams, which are shaping network execution through the development and application of innovative labor & flow planning mechanisms. Our goal is to improve and enhance the Amazon Fulfillment network to ultimately drive the best customer experience in a reliable and cost-efficient manner that is truly world-class.

As part of the PLEX organization, you’ll partner closely with other scientists, engineers, and product teams in a collegial environment to build optimization strategies that will influence the performance of all North America Amazon Fulfillment networks. You will develop scientific models and perform complex mathematical research to accurately solve labor and flow planning problems, enhance automation, and provide value-added research to the business. You will continually iterate and identify new modeling and research opportunities to implement science into customer fulfillment planning processes.

We are looking for a passionate scientist with a commitment to innovation & teamwork. Successful candidates will have a deep knowledge of optimization techniques and ML methods to tackle complex science problems. You will have the communication skills necessary to impact and influence leadership & partner teams through technical writings, presentations and discussions. You will learn a lot, grow, and have fun in the process!

Innovation Opportunities & Career Growth

Our business grows fast and we want our employees growing with it too. We provide constant opportunities for growth in our team through regular training, talent development, mentoring, and mechanisms conducive to incubating ideas from the bottom up to showcase your innovations.

Inclusive Team Culture

Here at Amazon, we promote an inclusive and engaging environment. We understand the strength that unique experiences bring to the team and value it. In our team, we uphold that all individuals should feel included, respected, and developed.

Flexibility

It's not the hours that you put into work matters, rather it's the quality of work that you put in. We provide flexibility and support to help you find a balance between your work and personal lives.

This position will be based in Austin, TX We are open to hiring candidates to work out of one of the following locations:

• Austin, TX

• Bellevue, WA

• Nashville, TN

Key job responsibilities

• Create & improve mathematical optimization techniques & ML models for labor & flow planning

• Lead & partner with research, applied, and data science teams to improve accuracy of existing technology solutions and provide data driven recommendations for strategic model implementations

• Identify and thoroughly research external and previously non-considered factors to implement with advanced mathematics

• Simplify the scientific decisions by navigating through the technology complexities, explaining them in plain customer and business context to our partners & customers.

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | Bellevue, WA, USA | Nashville, TN, USA

Basic Qualifications

• PhD or Master's degree with 3+ years of experience in computer science, mathematics, statistics, machine learning or equivalent quantitative research field

• Experience in mathematical optimization, machine learning, statistics, and deep learning

• Experience working with cross-functional teams & stakeholders

• Experience analyzing both experimental and observational data sets

Preferred Qualifications

• Strong understanding of statistical analysis and machine learning techniques, including deep learning and neural networks

• Experience consulting with senior leadership and executives in a fast-paced environment

• Experience investigating the feasibility of applying scientific principles and concepts to large-scale business problems and products

• Knowledge of programming languages such as C/C++, Python, Java or Perl

• Experience with agile development

• Have publications at top-tier peer-reviewed conferences or journals

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $100,400/year in our lowest geographic market up to $195,200/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.