Description
- 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
- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior leadership
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.
Automated Inventory Management (AIM) team is seeking for an experienced Sr. Business Intelligence Engineer to lead Supply Chain projects for LATAM (Brazil and Mexico) being based in Brazil. This strategic role will be analyzing large sets of data to build insights and help making data-driven decisions. The Sr. BIE will work with Operations, business teams and other stakeholders to create metrics, track goals and implement projects. The BIE candidate should be comfortable working within a cross functional environment, supporting multiple stakeholders and initiatives. The candidate must have a true hands-on approach, strong analytical skills, including the ability to gain true insights from data, and be an effective communicator.
Key job responsibilities
- Work with teams in the organization to identify opportunities and build analytical solutions that provide them with decision making capabilities and insights.
- Partner extensively with Supply Chain and Operations teams proactively identify analytical needs, translate them to BIE/Science solution designs.
- Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations that will help shape the direction of analytics projects/ products.
- Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions. Ensure data accuracy by validating data for new and existing tools.
- Design and influence operational best practices for reporting and predictive analytics to enable the team to scale.
- Root cause analysis and uncovering core issues using data, then assisting to create new measures for the wider Amazon team
- Manage and execute entire projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.
- Collaborate with Product and Program management teams to design analytics frameworks that will support large-scale data-analysis and on-ground corrective actions.
- 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
- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior leadership
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.
Automated Inventory Management (AIM) team is seeking for an experienced Sr. Business Intelligence Engineer to lead Supply Chain projects for LATAM (Brazil and Mexico) being based in Brazil. This strategic role will be analyzing large sets of data to build insights and help making data-driven decisions. The Sr. BIE will work with Operations, business teams and other stakeholders to create metrics, track goals and implement projects. The BIE candidate should be comfortable working within a cross functional environment, supporting multiple stakeholders and initiatives. The candidate must have a true hands-on approach, strong analytical skills, including the ability to gain true insights from data, and be an effective communicator.
Key job responsibilities
- Work with teams in the organization to identify opportunities and build analytical solutions that provide them with decision making capabilities and insights.
- Partner extensively with Supply Chain and Operations teams proactively identify analytical needs, translate them to BIE/Science solution designs.
- Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations that will help shape the direction of analytics projects/ products.
- Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions. Ensure data accuracy by validating data for new and existing tools.
- Design and influence operational best practices for reporting and predictive analytics to enable the team to scale.
- Root cause analysis and uncovering core issues using data, then assisting to create new measures for the wider Amazon team
- Manage and execute entire projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.
- Collaborate with Product and Program management teams to design analytics frameworks that will support large-scale data-analysis and on-ground corrective actions.
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