Applied Scientist II, Inbound Forecasting
DESCRIPTION
Amazon has the world’s most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. A core part of the operations is forecasting: We forecast the demand of hundreds of millions of products up to a year into the future. The forecasts are used to automatically order hundreds of millions worth of inventory weekly, decide where to place that inventory, and to establish labor plans for hundreds of warehouses.
The Applied Scientist II will work with the Supply Chain Optimization Technologies (SCOT) Forecasting team and both business and engineering stakeholders worldwide to develop state of art machine learning models to forecast inbound shipment. The scientist develops novel algorithmic architectures, toward the ultimate goal of accurately predicting when and how Amazon receives shipments of millions of products world-wide. This drives down costs and enables the offer of lower prices and better in-stock selection for our customers.
Working collaboratively, you will develop solutions to complex problems, such as designing the next generation of algorithms. As an Applied Scientist, you will continue to contribute to the research community, by working with other scientists across Amazon, as well as collaborating with academic researchers and publishing papers. Within SCOT Forecasting, our Science community values teamwork and recognizes the need to take chances and try new ideas that may fail. Furthermore, our builder culture means that Scientists and Software Development Engineers work closely together to invent and construct at a massive scale. Your work can be part of Amazon production system and result in concrete business impact.
Key job responsibilities
- Design, implement, and evaluate innovative models, agents, and software prototypes.
- Collaborate with a team of experienced scientists to drive technological advancements.
- Develop novel solutions to complex business problems in collaboration with partner teams.
- Constructively critique peer research and mentor junior scientists and engineers
- Contribute to Amazon's global science community through collaboration and publication of groundbreaking research.
About the team
Supply Chain Optimization Technologies (SCOT) owns Amazon’s global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We decide how to place and move inventory within Amazon’s fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of world-wide. Venturing beyond traditional operations research methods for sequential decision-making in inventory planning. The team combines empirical research and real world testing, backed by a robust theoretical foundation.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience in professional software development
- PhD in math/statistics/engineering or other equivalent quantitative discipline
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
- If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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.