Senior Applied Scientist

Job ID: 1597835 | Amazon.com Services LLC

DESCRIPTION

Are you interested in big data, machine learning, and product recommendations? If so, the Product Semantics team in Amazon Product Graph might be the right place for you. We are a team in a fast-paced organization with a huge impact on hundreds of millions of customers. We innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems.

As the world’s most customer-centric company, Amazon heavily invests in inventing and applying state-of-art technologies to build world-class product recommendation systems to improve shopper experience. We break fresh ground to create world-class customer-facing features to help customers discover high quality products that meet their needs, and provide most relevant product information to help customers make confident shopping decisions. We are a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we have a very wide range of new opportunities to explore.

The Product Semantics team in Amazon Product Graph, based in Seattle and New York City, is looking for scientists who love big data, are passionate about understanding products and product relationships from product profiles, reviews, and search log, and who are capable of inventing and applying Machine Learning, NLP, and Computer Vision techniques that will leave no valuable data behind. Our applied scientists work closely with software engineers to put algorithms into practice. They also work in partnership with teams across Amazon to create enormous benefits for our customers.

The Product Semantics team in Amazon Product Graph, based in Seattle and New York City, is looking for Applied Scientists who love big data, are passionate about understanding products and product relationships from product profiles, reviews, and search log, and who are capable of inventing and applying Machine Learning, NLP, and Computer Vision techniques to solve real world problem and serve customer-facing features on Amazon. Our applied scientists work closely with software engineers to put algorithms into practice. They also work in partnership with teams across Amazon to create enormous benefits for our customers.

If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.

Key Responsibilities

- Use machine learning and analytical techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes
- Design, development and evaluation of highly innovative models for predictive learning
- Work closely with software engineering teams to drive model implementations and new feature creations
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Research and implement novel machine learning and statistical approaches

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
· 3+ years of hands-on experiences in NLP, Recommendation, Search, Machine Learning or a related field
· Strong algorithm development experience and problem solving ability
· Strong communication and data presentation skills.

PREFERRED QUALIFICATIONS

· 10+ years of relevant experience in industry and/or academia.
· Publications in top venues such as KDD, ICML, NeuIPS, WWW, WSDM
. Experience with distributed systems for processing large data is a plus
. Familiar with Hadoop, Spark, Hive/Pig will be a plus.