Principal Applied Scientist, Amazon Stores Economics & Science (SEAS)

Principal Applied Scientist, Amazon Stores Economics & Science (SEAS)

Job ID : 2799703 | Amazon.com Services LLC

Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly.

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission : we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning using LLMs. We are looking for a seasoned Applied Science leader to build and deliver cutting-edge science and engineering solutions to improve our Stores business. In this role, you will lead a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing the scientific models, benchmarks, and services. Graduate education and hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a must. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity.

Key job responsibilities

Knowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.

BASIC QUALIFICATIONS

• 10+ years of building machine learning models for business application experience
• PhD, or Master's degree and 10+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS

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.

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