Sr Data Scientist

Job ID: 1186225 | Amazon.com Services LLC

DESCRIPTION

How often have you had an opportunity to be a member of a team that is tasked with solving customer needs through disruptive and innovative technology? Everyone on the team needs to be entrepreneurial, wear many hats and work in a fast-paced, ambiguous, and highly collaborative environment that’s more startup than big company. If this sounds intriguing, then we’d like to talk to you about a role on the Amazon WWDE team.

The Customer Service Worldwide Defect Elimination (WWDE) organization drives Amazon towards a defect-free customer experience by building technology that rapidly identifies defects, associates them with the information required to resolve the root cause, and prioritizes the multitude of improvement opportunities based on business and customer needs. To continue expanding our defect elimination program, WWDE is seeking a passionate, results-oriented Data Scientist

The Data Scientist will work closely with other research scientists, machine learning experts, and economists to design and run experiments, research new algorithms, and find new ways to improve last mile analytics to optimize the Customer experience. The Scientist will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. Science at Amazon is a highly experimental activity, although theoretical analysis and innovation are also welcome. Our scientists work closely with software engineers to put algorithms into practice. They also work on cross-disciplinary efforts with other scientists within Amazon.

The key strategic objectives for this role include:
· Understanding drivers, impacts, and key influences on Pricing dynamics.
· Optimizing Seller Pricing to improve the Customer experience and grow the Amazon business.
· Drive actions at scale to provide low prices and increased selection for customers using scientifically-based methods and decision making.
· Helping to build production systems that take inputs from multiple models and make decisions in real time.
· Automating feedback loops for algorithms in production.
· Utilizing Amazon systems and tools to effectively work with terabytes of data.

BASIC QUALIFICATIONS

·
· Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
· 5+ years of experience working in data science in a consumer product company, managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists
· 3+ years of experience as a manager of managers
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
· Experience hiring and leading experienced scientists as well as a successful record of developing junior members to a successful career track
· Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

PREFERRED QUALIFICATIONS

· A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
· 10+ years of experience working in data science in a consumer product company
· 5+ years of experience managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists
· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval, XGBoost, LightGBM, ElasticNet.
· Skilled with Java, C++, or other programming language, as well as with R, SAS, MATLAB, Python or similar scripting language
· Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker.
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval
· Advanced knowledge and expertise with Data modelling skills, Advanced SQL with Oracle, MySQL, and Columnar Databases
· Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
· Demonstrated industry leadership in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing.
· Deep understanding of data, application, server, and network security

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age