DESCRIPTION

Play a key role in the adoption of Amazon Private Brands by working on a range of challenging problems related to discovery, selection and customer feedback. Working closely with a team of software engineers, and product managers, you will help solve hard problems in the Private Brands space. These include: How can customers discover Private Brands in existing locations; what products are we missing in our selection today that can be successful as a private brand; how do we surface the right product information from existing data for customers to make informed choices and set the right expectations.

Private Brands (Amazon Brands such as Solimo, Amazon Basics, Amazon Elements, Mama Bear, Happy Belly, Presto) is one of the top initiatives with Amazon Retail with aggressive business goals in terms of product discoverability, customer acquisition and retention. Our vision is to provide value to Amazon customers through highly-rated, highly-profitable products. The Private Brands tech team is seeking an Applied Scientist willing to work on a range of problems with aggressive priorities and help launch these features in prod.

As an Applied scientist, you will provide machine learning leadership to the team that helps accelerate the business. You will build machine learning models that help us innovate different ways to enhance customer experience. You will need to be entrepreneurial, wear many hats, and work in a highly collaborative environment. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.
Responsibilities:

• Drive collaborative research and creative problem solving
• Constructively critique peer research and mentor junior scientists and engineers
• Create experiments and prototype implementations of new learning algorithms and prediction techniques
• Collaborate with engineering teams to design and implement software solutions for science problems
• Contribute to progress of the Amazon and broader research communities by producing publications

BASIC QUALIFICATIONS

• Ph.D./M.S. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
• 3+ years of hands-on experience in predictive modeling and analysis
• 3+ years hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
• 1+ years professional experience in software development
• Proficiency in model development, model validation and model implementation for large-scale applications
• Ability to convey mathematical results to non-science stakeholders
Strength in clarifying and formalizing complex problem

Amazon Science gives you insight into the company's approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It's the company's ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

Please visit https://www.amazon.science for more information

PREFERRED QUALIFICATIONS

• Ph.D. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
• 7+ years of practical experience applying ML to solve complex problems in an applied environment
• Significant peer-reviewed scientific contributions in premier journals and conferences
• Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
• Experience with defining research and development practices in an applied environment
• Proven track record in technically leading and mentoring scientists
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

Amazon Science gives you insight into the company's approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It's the company's ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

Please visit https://www.amazon.science for more information.