Senior Applied Scientist, Selection Monitoring Amazon Jobs – Seattle, WA

Amazon.com Services LLC

Amazon jobs in Washington State, United States – Apply for Senior Applied Scientist, Selection Monitoring Amazon Jobs – Seattle, WA. See the job description, requirements, and the link to apply.

Job ID: 2287683

Job Title: Senior Applied Scientist.

DESCRIPTION

Job summary
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 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.
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.

Key job 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

A day in the life

  • You will work with Product Managers to translate the business problem into a science problem
  • You will define methods for data collection and performance evaluation
  • You will experiment new models and evaluate their performance
  • You will perform deep dive to understand potential issues impacting model performance, and form hypotheses for improvement
  • You will help deploy the model into production
  • You will communicate your experimental and production result to Product Managers and business stakeholders

About the team
We are a group of innovators that thrive in creating customer impact!

BASIC QUALIFICATIONS

 

  • PhD degree with 4+ years of applied research experience or a Master’s degree and 6+ years of experience of applied research experience
  • 3+ years of experience in building machine learning models for business application
  • Experience programming in Java, C++, Python or related language

 

PREFERRED QUALIFICATIONS

 

  • PhD. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
  • 7+ years of hands-on experience in predictive modeling and analysis
  • 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
  • Proficiency in model development, model validation and model implementation.
  • 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.
  • 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.
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