DESCRIPTION

Interested in driving thought leadership by building machine learning solutions that will derive actionable insights about the complex economy of Amazon’s retail business? Whether you’re passionate about building highly scalable and reliable systems or a scientist who likes to solve novel business problems, the Negotiations AI team is the place for you. NAI uses machine learning, generative AI, causal inference, and econometric/economic modelling to analyze Amazon’s relationships with vendors, and recommend actions that generate mutual growth. We are an interdisciplinary team of applied scientists, engineers, and economists building solutions to solve some of the toughest business problems at Amazon.

As a senior Applied Scientist, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into scalable solutions. You use your broad experience with a diversity of machine learning methods to determine the right approach to solve complex business problems that can have humans-in-the-loop and may be data sparse. You provide feedback to other scientists on the team, help them define problems and solutions, and mentor junior scientists. You’re committed to on-going learning and can quickly acquire the knowledge you need to address novel problems. You work effectively with science, engineering, economics and business teams.

Key job responsibilities
– Apply machine learning and modeling techniques including deep learning, generative AI, reinforcement learning and causal inference methods to automate negotiation processes and drive business growth for Amazon and its vendors
– Work with business subject-matter-experts (SMEs) to develop models that support human decision making during complex business negotiations
– Design experiments and metrics that can quantify the impact of models on business outcomes
– Collaborate with engineering teams to design and implement software solutions for science problems
– Contribute to Amazon and broader research communities by producing publications

BASIC QUALIFICATIONS

– 3+ years of building machine learning models for business application experience
– PhD, or Master’s degree and 6+ 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

– 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.

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.

USA, WA, Seattle