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Bie Fleet Optimization, Last Mile Rentals Expansion
il y a 1 mois
Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with SQL
- Experience in the data/BI space
Amazon Logistics is seeking a BIE Fleet Optimization FTC (6 month contract) to work in the EU Fleet Procurement and Capacity (FPAC) organization..
A successful BIE in this team will build tools and systems, and deliver critical insight to drive transformation alongside a team of Program Managers. The Fleet Optimization BIE will focus on introducing new metrics and answering the key question on what is the right way to measure our fleet utilization and manage our cost base. They will be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so.
The position can be located in Madrid, London, Munich, Berlin, Paris or Milan.
Key job responsibilities
- Create innovative solutions using data and research to address wider challenges in your organisation
- Take a big-picture approach in your analysis of business operations, driving improvements across a range of teams and organisations
- Work alongside senior leadership to establish and prioritise improvement programs, seeing them through from start to finish
- Enhance operational performance on every programs in partnership with your stakeholders
A day in the life
The Last Mile Rentals (LMR) expansion team work with external suppliers to bring to fleet sharing programs to Amazon Logistics. The role is at the forefront of enabling a more flexible fleet.
Luxembourg, LUX
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
