The Selling Partner Communities (SPC) organization is dedicated to ensuring every Selling Partner (SP) achieves satisfaction with their Amazon selling experience. SPC serves as a vital bridge between sellers/vendors and Amazon, creating and managing platforms where they can connect, share knowledge, and receive help. The team's mission encompasses listening to SP feedback, advocating for experience improvements, and empowering SPs through effective, relevant, and timely communications that demonstrate Amazon's commitment to building lasting partnerships.
We are seeking a Sr. Applied Scientist to join our Communities team. The successful candidate is a skilled scientist capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment.
Key job responsibilities
The Senior Applied Scientist in the Selling Partner Communities (SPC) organization plays a crucial role in developing and implementing advanced AI and machine learning solutions to enhance the selling partner experience on Amazon. This role requires strong ownership of all technical aspects throughout the full project lifecycle, while partnering closely with the business to define requirements and exercise good judgment in balancing speed and complexity. As a senior AS on our team you will:
- Handle challenging problems that directly impact millions of selling partners
- Independently collect and analyze data
- Design, develop and deliver scalable models, using any necessary programming, machine learning, and statistical analysis software
- Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research
- Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software
- Participate in design and implementation across teams to contribute to initiatives and develop optimal solutions that benefit the SPC organization
- Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.
About the team
The Selling Partner Communities (SPC) organization serves as a vital bridge between SPs and Amazon, creating and managing platforms where sellers can connect, share knowledge, and receive help. The team's mission encompasses listening to feedback, advocating for experience improvements, and empowering SPs through effective, relevant, and timely communications that demonstrate Amazon's commitment to building lasting partnerships.
Within SPC, the Science team plays a critical role in leveraging artificial intelligence and machine learning technologies to enhance seller experiences and drive data-driven decisions. The team serves as technical advisors helping shape the organization's scientific vision and strategy, identifying and tackling intrinsically hard, previously unsolved problems that require novel scientific approaches. The team focuses on developing comprehensive frameworks for measuring and monitoring seller sentiment, improving content discovery and engagement, enhancing operational efficiency for Community Assistance Managers (CAMs), bringing clarity to complex challenges through scientific expertise, and creating AI-powered tools for content generation and validation.
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.
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
- Experience identifying opportunities to integrate AI solutions into products and services to drive business value
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at ;br>
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: RESLBFEED
- Position Id: 21523_28119_10388646
- Posted 1 day ago
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