Principal Machine Learning Scientist

US-WA-Seattle
11 months ago
Job ID
462914
Amazon Corporate LLC
Position Category
Research Science

Job Description

Are you experienced at applying machine learning to big-data tasks? Are you excited by analyzing and modeling terabytes of text, images, and other types of data to solve real-world problems? We love data and we have lots of it. Join a high impact innovative team of scientists, economists and engineers who use Machine Learning, Statistics and Econometrics to develop highly innovative and impactful products that influence the company’s bottom line.

The Central Economics team supports the executives to drive the global optimization across almost all key business units of Amazon, including market design, pricing, forecasting, online advertising, search, supply chain network planning, and other areas. Our team is building a number of highly innovative and impactful products, such as Amazon Economics Intelligence Service, Amazon Search/Discovery optimization, and Amazon Corporate Bridging Service. Join us to build revolutionary products that has significant impact of the company’s footprint. We are looking for versatile and passionate scientists who want to develop industry leading technologies and set the bar for every other company.

As a principal machine learning scientist, you guide a team of scientists about technology and research directions. You will work on projects of large opportunities. You will collaborate with economists, engineers and product teams. Your work will have a direct impact on the bottom line of our business while improving customer experience. If big data, cutting edge technologies and building intelligent systems excite you, if you love to innovate and deliver results, then we want you to be on our team.

Major responsibilities

  • Use machine learning and statistics techniques to create scalable solutions for business problems
  • Analyze and extract relevant information from large amounts of both structured and unstructured data to help automate and optimize key processes
  • Design, experiment and evaluate highly innovative models for predictive learning
  • Work closely with software engineering teams to drive real-time model experiments, implementations and new feature creations
  • Work closely with business staff to optimize various business operations
  • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
  • Track general business activity and provide clear, compelling management reporting on a regular basis
  • Research and implement novel machine learning, statistical and econometrics approaches
econjobs

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

Basic Qualifications

  • PHD in CS Machine Learning, Statistics, or in a highly quantitative field
  • Solid background in statistical learning techniques
  • Algorithm implementation experience as well as the ability to modify standard algorithms (e.g. changing objectives, working-out the math, implementing and scaling)
  • Strong programming skills in at least one object oriented programming language (Java, Scala, C++, Python, R, etc.). Experience in implementing the models that handle terabytes of data.
  • Knowledge of or experience in building production quality and large scale deployment of applications related to machine learning.
  • Fluency with Unix systems
  • Ability to develop prototypes by manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
  • Proven record of delivering results
  • Strong communication and data presentation skills
  • Strong problem solving ability

Preferred Qualifications

  • 10+ years of industry experience in machine learning and large data analysis
  • Experience with building chatbot
  • Experience with boosting, deep learning and sequence modeling
  • Experience developing causal modeling
  • Experience in system development in Spark and MLlib

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