Role at a glance
- Job function
-
AI & Data AI Research & Applied Science
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Experience
- Senior Level 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
- Education
- PhD, or Master's degree and 6+ years of applied research experience
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Senior Applied Scientist identifies data-driven opportunities to improve seller recruitment and growth, developing scientific solutions and collaborating with engineering, research, and business teams. The role leads complex science projects, contributes to research, and communicates scientific innovations to internal and external audiences.
What You'll Do
- Identify opportunities to improve selling partner growth and translate them into statistical and machine learning problems.
- Mentor and guide applied scientists, maintaining high standards for technical rigor and MLOps.
- Design and lead roadmaps for complex science projects that support seller experience and long-term shopper value.
- Work with engineering partners to address latency and other system constraints.
- Identify and drive high-risk technical and scientific research directions through to delivery.
- Communicate scientific innovations to the broader internal and external scientific community.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Requires 4+ years of applied research experience and 3+ years building machine learning models for business applications, or a PhD; alternatively, a Master's degree with 6+ years of applied research experience. Requires programming experience in Java, C++, Python, or a related language, and experience with neural deep learning methods and machine learning.
Preferred
- 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...
- Experience identifying opportunities to integrate AI solutions into products and services to drive business value
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.