Job Description

DESCRIPTION

About Amazon.com:
Amazon.com strives to be Earth\'s most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a world-class e-commerce platform. Amazon\'s evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company\'s DNA. The world\'s brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world.

About Team
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns).

Overview of the role
As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to entity extraction for Catalog completeness and consistency, supervised and unsupervised techniques, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results.

Key job responsibilities

• Collaborate with seasoned Applied Scientists and propose best in class ML solutions for business requirements
• Dive deep to drive product pilots, demonstrate think big and customer obsession LPs to steer the product roadmap
• Build scalable solutions in partnership with Applied Scientists by developing technical intuition to write high quality code and develop state of the art ML models utilizing most recent research breakthroughs in academia and industry
• Coordinate design efforts between Sciences and Software teams to deliver optimized solutions
• Ability to thrive in an ambiguous, uncertain and fast moving environment
• Mentor Junior Research Analyst (RAs) and contribute to RA hiring

Basic Qualifications

• Bachelor\'s degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics)
• 1+ years of relevant work experience in solving real world business problems using machine learning, deep learning, data mining and statistical algorithms
• Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory
• Strong analytical thinking
• Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills
• Ability to collaborate effectively across multiple teams and stakeholders, including development teams, product management and operations.

Preferred Qualifications

• Master\'s degree with specialization in ML, NLP or Computer Vision preferred
• 1+ years relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis)
• Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in Data science, ML and Statistics

About the team
RBS works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our sciences (ML/AI) and platform teams help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). As a Sciences team, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to entity extraction for Catalog completeness and consistency, supervised and unsupervised techniques, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. RBS Sciences team has grown to 11+ Applied Scientists and created multi-million dollar impact by developing foundational models for these business problems. Team has also contributed significantly in innovation space by publishing research papers (both internal Amazon and external conferences) and Patents over last 3 years.

BASIC QUALIFICATIONS

• Bachelor\'s degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics)
• 1+ years of relevant work experience in solving real world business problems using machine learning, deep learning, data mining and statistical algorithms
• Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory
• Strong analytical thinking
• Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills
• Ability to collaborate effectively across multiple teams and stakeholders, including development teams, product management and operations.

PREFERRED QUALIFICATIONS

• Master\'s degree with specialization in ML, NLP or Computer Vision preferred
• 1+ years relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis)
• Diverse experience will be favored eg. a mix of experience across different roles
• In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service
• Technical expertise, experience in Data science, ML and Statistics
• Demonstrated skill in serving as a change agent
• Demonstrated skill in working in ambiguous and fast paced environments

Amazon