Senior Data Scientist, Selling Partner Experience Science Team

Description

Do you want to join an innovative team of scientists who use machine learning to help Amazon provide the best experience to our Selling Partners by automatically understanding and addressing their challenges, needs and opportunities? Do you want to build advanced algorithmic systems that are powered by state-of-art ML, such as Natural Language Processing, Large Language Models, Deep Learning, Computer Vision and Causal Modeling, to seamlessly engage with Sellers? Are you excited by the prospect of analyzing and modeling terabytes of data and creating cutting edge algorithms to solve real world problems? Do you like to build end-to-end business solutions and directly impact the profitability of the company and experience of our customers? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Selling Partner Experience Science team.

Key job responsibilities

Use statistical and machine learning techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.

Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions.

Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features.

Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.

Research and implement novel machine learning and statistical approaches.

Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.

About the team

Selling Partner Experience Science is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. Focused on collaboration, innovation and strategic impact, we work closely with other science and technology teams, product and operations organizations, and with senior leadership, to transform the Selling Partner experience.

Basic Qualifications

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical / mathematical software (e.g. R, SAS, Matlab, etc.) experience

4+ years of data scientist experience

Experience with statistical models e.g. multinomial logistic regression

Preferred Qualifications

Experience managing data pipelines

Experience as a leader and mentor on a data science team

Experience using cloud architecture to scale data science algorithms

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country / region you're applying in isn't listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300 / year in our lowest geographic market up to $247,600 / 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 . This position will remain posted until filled. Applicants should apply via our internal or external career site.