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Amazon
Do you want to join an innovative team of engineers and analysts who use machine learning and analytical techniques to create state-of-the-art solutions for providing better value to Amazon's Sellers, Vendors, and Customers? Are you excited by the prospect of analyzing large amounts of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Business Intelligence and Analytics team for Support Operations.
As a business intelligence engineer, there are lots of opportunities for you to make an impact. Your talent is wanted to make data accessible to modeling -- our models cannot go very far without good data.
You will design and implement streamlined data pipelines that can scale for volume, velocity, variety, and veracity. Your talent is wanted to make model results measured. You will build metrics and procedures to quantify their goodness and badness (much easier said than done). Your talent is wanted to democratize analytics. You will design and build dash- and visualization functionalities that will help our team members and business customers to explore complex multi-dimensional data produced by production systems as well as our models.
You should be a self-starter who knows and loves working with BI tools, and who thrives on implementing creative approaches and dealing with the intricate complexity of large data sets. You will also have the opportunity to display your skills in the following areas:
- Performing analysis and validation using mathematical optimization models for network design tasks
- Recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
- Partnering closely with other team members to solve analytical problems and working with customers to answer key business questions.
- Communicating with senior management as well as with colleagues from different backgrounds
Key job responsibilities
- Analyze and visualize transaction data to determine customer behaviors, and output solid analysis report with recommendation
- Design and drive experiments to form actionable recommendations. Present recommendations to business leaders and drive decisions. Also manage implementation of those recommendations.
- Build and design data pipelines and orchestrations design that can scale for volume, velocity, variety, and veracity.
- Develop metrics that helps support product category growth and expansion plans
About the team
The Support Operations team provides world-class support to the North America supply chain with initiatives that require complex investigation. With a mix of operational and program expertise, Support Ops works with various stakeholders to investigate and resolve supply chain issues, while minimizing the overall business risk and maintaining the high Amazon quality bar.
Support Ops Analytics is dedicated to delivering timely data insights to the leaders of Support Operations. We create dashboards, reports, and data pipelines to enable our stakeholders to move as quickly as possible in meeting our goals while maintaining a quality selling partner experience.
Training & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.- 10+ years of professional or military experience
- 5+ years of SQL experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval, data science, machine learning and data mining
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