Applied Scientist

Job ID: 1311900 | Amazon.com Services LLC

DESCRIPTION

#FoundItOnAmazon is to be an upper funnel browsing experience designed to show customers an endless stream of inspirational products. It is a companion to Amazon's search experience and is meant to drive habitual interaction on Amazon and lead to serendipitous purchases. It is deliberately diverse, visually engaging, and meant to encourage customers to experience the thrill of the hunt. Our vision is for #FoundItOnAmazon to be the first destination for customers to find inspiration and drive customers to visit Amazon more often. #FoundItOnAmazon provides inspiration that converts to purchases, and collects engagement signals (follow, hearts) that can improve the customer’s experience across Amazon.

The team is looking for an Applied Scientist to be based in Seattle area. As a key member of the team, you will provide machine learning expertise that helps accelerate the business. You will build various data and machine learning models that help us innovate different ways to enhance the 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.

An ideal candidate will be an expert in the areas of machine learning and statistics who will have expertise in applying theoretical models in an applied environment. The candidate will be expected to work on numerous aspects of Machine Learning such as feature engineering, predictive modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models including transfer learning. Challenges will involve dealing with very large data sets and requirements on throughput.

Responsibilities include:
· Design, implement, test, deploy, and maintain innovative data and machine learning solutions to accelerate our business.
· Create experiments and prototype implementations of new learning algorithms and prediction techniques
· Collaborate with scientists, engineers, product managers, and stockholders to design and implement software solutions for science problems
· Use machine learning best practices to ensure a high standard of quality for all of the team deliverables

BASIC QUALIFICATIONS

· 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
· 2+ years of hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
· 1+ years of 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 problems
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

PREFERRED QUALIFICATIONS

· Ph.D. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 5+ 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
· Excellent interpersonal communication with strong verbal / written English skills

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.