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Posted: Wednesday, May 10, 2017 5:26 AM

AWS is revolutionizing technology and business and at the core of that revolution is the way we think about identities at enormous scale. At AWS Identity and Access, we rely on scientific judgement supported by modeling, statistical inference, time:series forecasting, machine learning, and graph algorithms to make critical decisions and provide actionable insights to our customers. WeA?re looking for a Data Scientist with unfettered curiosity and a drive to solve major research challenges at the intersection of business and engineering. You will be a key driver in taking an idea to experimentation to prototyping and then to implementation. You will perform machine learning at petabyte scale to identify patterns and anomalies. ResponsibilitiesBuild complex statistical models that learn from and scale to petabytes of dataAnalyze and extract relevant information from large amounts of AWS data; Then use machine learning and data mining techniques to create data driven models and solutions to identify patterns and anomalies.Work closely with software engineering teams to implement model solutionsWork closely with stakeholders to optimize various business objectivesResearch and implement novel machine learning and data mining approachesAmazon is an Equal Opportunity:Affirmative Action Employer : Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation **For more information on Amazon Web Services please go to **Build complex statistical models that learn from and scale to terabytes of data.Ability to extract and query very large data sets using Java, Python, SQL etc and successively refine applicable parameters to accurately express data trends, patterns and anomalies.Cares deeply about the story the numbers tell and can independently perform in:depth investigations of data problems employing statistical skills.Proficiency in several techniques including but not limited to: Decision Trees, Clustering, Bayesian methods, SVM, linear/non:linear programming, Probabilistic graphical models, Bagging and Boosting techniques, Random Forests mitment to rigorous testing and validation to ensure findings are consistent, accurate, and generalizableAbility to transform data into a usable state using appropriate tools and techniquesDemonstrated ability to take a project from idea to experimentation to prototype to implementationDemonstrate high degree of attention to detailsMasters in Computer Science, Statistics or a similar field3+ years of experience analyzing data, identifying patterns and anomaliesPhD in Computer Science, Statistics or a similar field5+ years of experience analyzing data, identifying patterns and anomaliesExperience with Large Scale distributed Data processingExperience with service:oriented architecture and web servicesStrong customer focus, ownership, urgency and drive.


• Location: Seattle

• Post ID: 46592113 seattle is an interactive computer service that enables access by multiple users and should not be treated as the publisher or speaker of any information provided by another information content provider. © 2017