- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $74,100/year in our lowest geographic market up to $165,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technologies organization is for you.
Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot
The Amazon SCOT organization is expanding our Direct Fulfillment (dropship) business and we are looking for a Senior Business Intelligence Engineer to join the team. Direct Fulfillment helps provide Amazon customers the broadest in-stock selection, at the quality and speed of delivery they have come to expect from Amazon at the best possible cost structure for Amazon. Direct Fulfillment allows Amazon to fulfill customer orders directly from our vendor’s warehouse and is one of the fastest growing supply channels at Amazon.
The ideal candidate relishes working with extremely large volumes of data, enjoys the challenge of highly complex technical contexts, and above all, is passionate about data and analytics to impact business decisions. They should have strong analytical skills, independently blend data from multiple sources, drive consensus and connect business to data. They must also be passionate about partnering with the data scientists, business analysts and other business stakeholders & dive deep to identify root causes and provide actionable insights.
They should be comfortable with technologies like EMR, Redshift and have ability to author complex dashboards that enable business to cut through noise. They should be a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), excellent communication skills and enjoys working in a fast-paced and global team.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age
Key job responsibilities
- Deep dive into operations execution and business problems, use analytical and statistical rigor to identify trends and opportunities to driv data-driven decisions
- Improve business results through creating best-in-class metrics, analysis, visualizations, and data-driven storytelling
- Adopt best practices in reporting and analysis: data needs, data integrity, test design, analysis, validation, and documentation
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