Senior Applied Scientist, Selling Partner Selection Success

Amazon Inc.; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Job summary

Amazon is seeking a Senior Applied Scientist to lead data-driven improvements in Selling Partner recruitment and success. You will craft ML/GenAI solutions, translate opportunities into scientific problems, and collaborate with engineering, research, and business teams to productionize AI-infused experiences for sellers.

You will guide a team of scientists, ensure technical rigor in ML Ops, and publish findings while advancing Amazon's research agenda across internal and external communities.

Qualifications

• 4+ years of applied research experience.
• 3+ years of building ML models for business applications.
• 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.

Responsibilities

• Identify opportunities to improve SP growth and translate into science problems via principled statistical solutions (ML, RL, GenAI and Agentics).
• Mentor and guide the applied scientists with high technical rigor and excellence in MLOps.
• Design and lead roadmaps for complex science projects to improve selling experience and long-term value for shoppers.
• Collaborate with engineering partners to meet latency and system constraints.
• Identify high-risk technical directions and simulate new research directions to drive to completion.
• Communicate science innovations to internal and external scientific communities.

Skills

Applied research

Machine learning

Programming (Java/C++)

Communication of insights

Education

PhD or MS with experience

Tools

Java

C++

Python

Neural networks

Job description

Senior Applied Scientist, Selling Partner Selection Success

Job ID: 10585576 | Amazon.com Services LLC

Join us in the evolution of Amazon’s Seller business! The Selling Partner Recruitment and Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP 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 Senior Applied Scientist to lead us to identify data-driven insight and opportunities to improve our SP recruitment strategy and drive new seller success. As a successful applied scientist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You are sophisticated user and builder that can leverage the latest scientific methods, including statistics, machine learning, deep learning and GenAI technology and are able to put them in production to answer specific business questions, 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 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 (www.aboutamazon.com/research).

Key job responsibilities

As a Sr. Applied Scientist in the team, you will:

• Identify opportunities to improve SP growth and translate those opportunities into science problems via principled statistical solutions (e.g. ML, RL, GenAI and Agentics).
• Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in MLOps.
• Design and lead 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.
• Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver.
• Be responsible for communicating our science innovations to the broader internal & external scientific community.

Basic Qualifications

• 4+ years of applied research experience
• 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.
• 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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 https://amazon.jobs/en/benefits .

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.
• 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.