Machine Learning jobs in United Arab Emirates

DESCRIPTION

The Sr. Business Intelligence Engineer role supports the Supply Chain Org with Network Planning Analytics.

You will support the Supply Chain network planning team by building, optimizing, and maintaining BI solutions that use data sets, queries, reports, dashboards, and analyses to improve the efficiency and speed of long-term planning decisions. You will seek input and guidance from team members on both the technology required and the business need to develop end products that enable effective, data-driven business decisions.

You will have the creative freedom to develop technical solutions that support the network planning team by providing more granular analyses on key data points that present challenges to FC Ops teams. This can cover a broad range of topics, from customer demand signals to inventory deep dives and transportation.

You will develop strategies for querying, processing, persisting, analyzing, and presenting data. Proficiency in SQL and the ability to maintain and refine complex ETL processes is required. You should be able to write secure, stable, testable, maintainable code with minimal defects and automate manual processes where possible with the help of industry analytics visualization tools (e.g., Excel, Tableau/QuickSight). This work is critical to maintaining accurate reporting mechanisms shared with multiple stakeholder teams.

You will develop and own algorithms that automate network planning and FC launch recommendations, including but not limited to the inventory transfer algorithm. Proficiency in automation processes and scripting is required.

You will partner with peer BIEs and work cross-functionally across teams that cover the breadth of long-term Network Planning to short-term Launch Execution. As part of this role, you will participate in design, scoping, and prioritization discussions for technical projects that support these teams.

Key Job Responsibilities
An Sr. Business Intelligence Engineer in Amazon's supply chain plays a crucial role in leveraging data to drive strategic decision-making and operational improvements. Key responsibilities include:

1. Designing and implementing complex data models, developing advanced analytics solutions, and creating insightful dashboards and reports.
2. Collaborating closely with cross-functional teams, including operations, finance, and product management, to identify opportunities for supply chain optimization.
3. Translating business requirements into technical specifications, conducting in-depth data analysis, and communicating findings to both technical and non-technical stakeholders.
4. Mentoring junior team members, driving best practices in data engineering and visualization, and contributing to the overall data strategy of the supply chain organization.

About the Team
The EU supply chain network planning team at Amazon is responsible for optimizing the company's logistics network across Europe. Our key responsibilities include designing and implementing strategic network plans to enhance efficiency and reduce costs. The team analyzes complex data sets to forecast demand, determine optimal inventory levels, and plan capacity across fulfillment centers, sortation centers, and delivery stations. We work on long-term projects to expand and improve the network infrastructure, considering factors such as geographic coverage, transportation costs, and customer delivery promise times. The team collaborates closely with operations, transportation, and finance teams to ensure alignment with business goals and customer needs. We also develop and maintain sophisticated models and tools for scenario planning, helping Amazon adapt to changing market conditions and business requirements in the European market.

BASIC QUALIFICATIONS

1. Experience programming to extract, transform, and clean large (multi-TB) data sets.
2. Experience with the theory and practice of design of experiments and statistical analysis of results.
3. Experience with AWS technologies.
4. Experience in scripting for automation (e.g., Python) and advanced SQL skills.
5. Experience with the theory and practice of information retrieval, data science, machine learning, and data mining.
6. Experience working directly with business stakeholders to translate between data and business needs.
7. Experience with SQL.
8. Experience with data visualization using Tableau, Quicksight, or similar tools.
9. Experience in the data/BI space.

PREFERRED QUALIFICATIONS

1. Experience managing, analyzing, and communicating results to senior leadership.

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