Supply Chain Engineering Intern

Applies entry level of subject matter knowledge to solve a variety of common business issues related to Engineering/Supply Chain subjects. Works on problems of single / moderate complexity. Acts as a team member providing analysis of information and limited project direction input. Exercises guided judgement within defined practices and procedures to determine appropriate action. Follows established guidelines and interpret policies. Evaluates unique circumstances and makes recommendations.

The studend will be trained and developed to perform tasks related to the Engineering area for Personal Systems Operations.

Supports engineering regular activities in the following areas:

• →Product Lifecycle Management (NPI – New Products Introduction, Sustaining, EOL – End of Life)
• →Bill of Materials (BOM) creation/setup/maintenance and Engineering Change coordination
• →Product and Production Quality Performance management
• →Ensure manufacturing efficiency, monitoring line performance and supporting capacity planning
• →Technical support to Desktops, Notebooks, Accessories & Displays manufacturing (Product, Test, Processes/Methods)
• →Measures engineering KPI’s and indicate improvement opportunities with lean manufacturing approach.
• →Supports the development of engineering dashboards/reporting with statistical approach.
• →Responsible for performing evaluation of product/process changes and resolve quality issues.
• →Collaborate with cross-functional teams, suppliers, and Manufacturing Partners (CM) to support operation and drive efficiency.
• →Test Systems implementation follow up
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Enrolled in Engineering college degree 

• Strong verbal and written communication skills. English language is desired
• Eager to learn, with high level of curiosity, combined with excellent teamworking skills. Proactive, self-motivated, and positive.
• Analytical thinking, technical analysis, and data manipulation skills.
• Demonstrated knowledge of Microsoft Office suite, especially of Excel and PowerPoint
• Possessing knowledge of Data Analytics and Visualization BI toolkits such Microsoft Power platform will be an added advantage.
• Notions of Lean Manufacturing, Quality Assurance and Data Validation techniques
• Knowledge of product life cycle management and production engineering theories.
• Technical and supply chain knowledge, particularly on manufacturing/production disciplines.
• Knowledge in automation, smart manufacturing is preferred but not a must.

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