Amazon’s International Seller Services organization is seeking an experienced Data scientist with excellent statistical and analytical abilities as well as data engineering skills. You are a self-starter, someone who thrives in a fast-paced and ever-changing environment, with an uncanny knack and passion for turning qualitative analysis and observations into diagnostics and metrics? Then you are the right candidate for our team.
Please visit https://www.amazon.science for more information
In this position, you will be a key contributor and sparring partner, developing analytics and insights that global executive management teams and business leaders will use to define global strategies and deep dive businesses. You will be part of a global team that is focused on acquiring new self-service merchants from around the world to sell on Amazon’s global marketplaces around the world. The position is based in Seattle but will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. You will also have the opportunity to display your skills in the following areas:
Be a thought leader: Interface with business partners, architect, design, implement, and support data science projects & tools that derive insights and shape important, worldwide business decisions.
Dive Deep, Raise the bar and insist on high standards: Recognize and adopt best practices in analysis and reporting, data integrity, test design, analysis, validation, and documentation. Support your leadership team with deep-dives and insights that improve our performance and productivity, so we can serve our customers even better.
Deliver Results: Be inspired by the motto of Customer First, use outstanding business acumen, technical and analytical skills to drive real, actionable results.
· Use statistical, econometric and machine learning techniques to create attribution models and measurement mechanisms.
· 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.
· Work closely with Economists and applied scientists to drive real-time model implementations and new feature creations.
· Work closely with operations staff to optimize various business operations.
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
Key job responsibilities
Key responsibilities for this role will include -
· Build prototype and production-ready machine learning models for classification, propensity, forecasting, causality and attribution problems
· Design, Build and Maintain scalable data pipelines required to productionalize machine learning models
· Perform deep dives and generate insights to identify improvement areas for models and business
· Build dashboards and other self-service tools useful for stakeholders
· Act as liaison between business stakeholders and Economist/Applied scientists
· Bachelor's degree
· 5+ years of experience working in data science roles
· 3+ years of experience applying machine learning techniques
· Skilled with Python, R, SAS, MATLAB, or similar scripting language
· Experience using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, demand modeling, etc.)
· Experience in distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Experience communicating verbally and in writing to technical peers and leadership teams with various levels of technical knowledge, educating them about systems and algorithms, as well as sharing insights and data-driven recommendations
· Experience querying, processing, filtering, and presenting large quantities (millions to billions of rows) of data.
· Masters or PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
· 5+ years of experience applying machine learning techniques
· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, recommendation systems, information retrieval
· Experience with Java, C++, or other programming language
· Proficient in SQL
· Functional knowledge of AWS tools such as S3, Sagemaker, Code Commit,
· Experience working in an Agile/Scrum environment.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.