Job Description

DESCRIPTION

In the Amazon Selection Monitoring team, we have the goal of establishing the most comprehensive, accurate and fresh universal selection of products. We enrich and increase the quality and coverage of Amazon product selection using cutting edge machine learning and big data technologies.

We are looking for highly motivated scientists who can lead the design, development, deployment and maintenance of data-driven models using machine learning (ML) and/or natural language (NL) and computer vision (CV) applications. Your models would be monitoring billions and billions of products. You will build Amazon scale applications running on Amazon Web Service (AWS) that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data.

Amazon Science gives you insight into the companys approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. Its the companys 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.
Responsibilities
Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understanding
Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential
Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps
Providing technical and scientific guidance to your team members
Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds
Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers

The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills.

BASIC QUALIFICATIONS

MSc. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
At least 5+ years of hands-on experience in predictive modeling and analysis
Proficiency in model development, model validation and model implementation.
At least 2+ years hands on experience programming in Java, Scala, C, C++ or other similar programming languages
Hands on experience with scripting languages such as Python
Work well in a fast-moving team environment and effectively deliver technical implementations having complex dependencies and requirements.

PREFERRED QUALIFICATIONS

PhD. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
7+ years of hands-on experience applying theoretical models in an applied environment
Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, Natural Language Processing, recommendation systems, dialogue systems, informational retrieval and Computer Vision
Hands on experience with distributed technologies such as MapReduce, Hadoop and Spark
Significant peer reviewed scientific contributions in premier journals and conferences
Proven track in leading, mentoring, and growing teams of scientists
Proven ability to work effectively in a cross-functional team
Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

Amazon is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation