The North American Retail Expansion Team is seeking an experienced and motivated Applied Scientist to work on driving strategic projects across multiple geographies. The environment is fast-paced with constant new challenges to solve.
The ideal candidate will have outstanding leadership skills, proven ability to develop, enhance, automate, and manage analytics models and data pipelines. The candidate will have strong data mining and modeling skills and will be comfortable facilitating idea creation and working from concept through to execution. This role will also build tools and support structures needed to analyze data and dive deep to determine root causes of systems errors. The candidate will also have the opportunity to present findings to cross functional team partners to drive improvements. The ideal candidate will have a proven ability to work with Research Scientists, Data Scientists, Software Development Engineers, Program Managers and Business Partners to solve challenging analytical problems. The candidate must be comfortable using intellect, curiosity and technical ability to develop innovative solutions to business problems. The position requires ability to learn different aspects of the business and understand how to apply advanced analytics to solve high impact problems.
A qualified candidate must have demonstrated ability to manage medium-scale automation and modeling projects, identify requirements and build methodology and tools that are mathematically grounded but also explainable operationally, apply technical skills allowing the models to adapt to changing attributes. Strong written and verbal communication skills are a must as this role will be in frequent contact with leadership. The person in this role will be expected to provide clear and concise explanation to results and approaches as well as provide opinion and guidance on problem solving.
* Manipulating/mining data from tables in S3 and Redshift. * Create automated metrics using Amazon supported tools: Quicksight and Datanet. * Providing analytical network support to improve quality and standard work results * Root cause research to identify process breakdowns within departments and providing solutions to breakdowns using data mining. * Foster culture of continuous improvement through feedbacks and metrics * Work with research scientists to use machine learning, data mining and statistical techniques to create new, scalable solutions for business problems
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