Applied Scientist II, Selling Partner Selection Success

About the role

Join us in the evolution of Amazon's Seller business! The Selling Partner Selection Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP selection growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources.

We are looking for a Applied Scientist II to work on our growth agent vision on seller recommendation to improve our SP growth strategy and drive new seller success.

As a successful Applied Scientist on our talented team of applied scientists and economists, you will leverage the latest scientific methods, including statistics, machine learning, deep learning and GenAI technology to solve complex problems, and collaborate with engineering, research, and business teams to deliver optimized experience (AI infused products, agentic experiences) on behalf of our sellers.

You need to have deep understanding on the business domain and have the ability to connect business with science. You are also strong in AI/ML/GenAI technology and scientific foundation with the ability to collaborate with engineering to put models in production to answer specific business questions.

You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers.

Key job responsibilities

As an Applied Scientist II in the team, you will

• Identify opportunities to improve SP growth and translate those opportunities into science problems via principled GenAI solutions.
• Design and execute roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers.
• Work with our engineering partners and draw upon your experience to meet latency and other system constraints.
• Be responsible for communicating our science innovations to the broader internal & external scientific community.

Basic Qualifications

• 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 using Unix/Linux
• Experience in professional software development
• 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

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

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.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually