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Research Scientist

Job Category:
Technology Provider
Career Level:
Mid Career (2+ years of experience)
Job Type:
Full Time/Permanent
Positions:
1
Company Name:
Amazon
City:
Seattle
Country:
USA
Description: Job Description
Be at the center of Amazon innovation with Amazon Local! This daily deals marketplace offers customers discounts of up to 75% off desirable goods and services in their communities -- over 100 regions throughout the United States. This rapidly-growing business within Amazon offers a creative, fast-paced, entrepreneurial work environment. 

We are looking for a practitioner in the Analytics field to a join a team of other research scientists who use data science/machine learning to build prediction and recommender systems that power the applications and business decisions for Amazon Local. The qualified candidate will call upon various supervised and unsupervised methods in order to: (1) analyze large datasets to identify attributes that directly influence deal quality, (2) understand customer preferences to generate predictions across various segments, and (3) build algorithms to automate predictive learning and drive real-time optimal recommendations. 
If you enjoy building models and have a track record of using data to deliver results then we would like to chat with you. 

Work responsibilities 
· Utilize advanced models to make predictions, uncover trends and automate pattern recognition
· Work closely with other scientists and SDEs to design, code, and test forecasting and optimization engines
· Monitor model performance and make enhancements to increase accuracy
· Generate ideas and new solutions that result in the creation of intellectual property
· Work closely with domain experts and mine data/text to generate new features
· Assist other teams in designing experiments to identify casual factors
· Run sampling, clustering, classification, etc on large datasets using a variety of analytics software (e.g. SAS, R, etc)
· Recommend KPI’s for Analytics applications, including dashboards and tools for exploratory data visualization
· Create, enhance, and maintain documentation for data, modeling choices, rationale and results
· Contribute to building the internal knowledge base on best practices in machine learning
· Identify areas for continuous improvement and research
· Be the thought leader on optimizing various business operations

Basic Qualifications
· Master’s Degree in a quantitative field
· Proficiency in several techniques including but not limited to: Decision Trees, GLM, Clustering, Bayesian methods, SVM, linear/non-linear programming, Multi-level models, Random Forests, Choice Models, etc.
· Competence in model-building/model-validation/scaling solutions in a production setting
· Proven ability to structure and analyze millions of rows of data
· Established expertise in exploratory data analyses 
· Comfortable mining unstructured data
· Applies rigor to justify arguments and reasoning 
· Demonstrated strong communication skills, both oral and written
· A natural curiosity and desire to learn
· Unwavering attention to detail
· Demonstrated ability to work effectively as part of a team

Preferred Qualifications
· PH.D in Machine Learning, Statistics, Operations Research, Data Science, Data Mining or equivalent
· Accounts for theoretical properties and assumptions of models when applying in practice
· Proficient in proto-typing models using scripting languages (e.g. Python, Ruby, etc.)
· 1+ year experience working in Java/C++ or other low level language 
· Experience with designing and building large-scale systems
· Knowledge of relational databases (SQL) and data warehousing processes, e.g. ETL
· Self-starter who is accountable for deliverables, capable of managing projects, and defining own design
· Natural language processing, information retrieval, and text mining experience is a plus