Description

The NA AMZL Supply Chain organization leads the innovation of Amazon’s Last Mile. We are an Operations org that hires and manages associates to deliver packages next day and sub-same day. The Execution and Planning Science (EPS) team sits within NA AMZL Supply Chain with the mission to build world-class automated Science-Tech products that enable ultra-fast delivery speeds for Amazon customers and job market opportunities for Amazon associates. Our key vision is to transform the online experience. We’re growing in scale and volume, by orders of magnitude. You will develop Science-Tech solutions to craft business strategy and roadmap to enable some of Amazon’s biggest brands to delight millions of customers. To succeed, we need senior technical leaders to forge a path into the future by building innovative, maintainable, and scalable systems.

At Amazon, we are constantly inventing and re-inventing to be the most associate-centric company in the world. To get there, we need exceptionally talented, bright, and driven people. Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers.

We are looking for a Senior Applied Scientist who will be the science lead for all key optimization initiatives, responsible for building models and prototypes for labor planning systems, and will require close collaboration with other scientists on the team that are developing state-of-the-art optimization algorithms to scale. This role spans the innovation pipeline - from identifying business needs, to developing new optimization and prediction techniques, to prototyping and implementation by working closely with colleagues in engineering, product management, operations, retail and finance

Key job responsibilities

As a Senior member of the scientist team, you will play an integral part on our Operations org with the following technical and leadership responsibilities:

• Help the team define the forward-looking Science roadmap and vision by helping to identify, disambiguate and seek out new opportunities

• Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements

• Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization

• Develop scalable models to derive optimal or near-optimal solutions to existing and new scheduling challenges

• Create prototypes and simulations to test devised solutions

• Advocate technical solutions to business stakeholders, engineering teams, as well as executive-level decision makers

• Work closely with engineers to integrate prototypes into production system

• Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features

• Mentor and supervise the work of junior scientists on the team for technical development and their career development and growth

• Present business cases and document models, analyses, and their results in order to influence important decisions

Basic Qualifications

• PhD, or Master's degree and 6+ years of applied research experience

• 3+ years of building machine learning models for business application experience

• Experience programming in Java, C++, Python or related language

• Experience with neural deep learning methods and machine learning

• 3+ years experience building optimization systems used at scale

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

• Experience with large scale distributed systems such as Hadoop, Spark etc.

• PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field

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 $150,400/year in our lowest geographic market up to $260,000/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.