Data Engineer Intern – Supply Chain Process Digitalization

Position Overview: The Data Engineer Intern will be a dynamic contributor to the supply chain team's digitization initiatives. They will leverage advanced analytics, machine learning, and artificial intelligence to drive innovation and efficiency in supply chain operations.

Project Brief:

• The project aims to create a SKU Data Master to streamline and enhance the management of SKU-related information. This project aligns with the strategic goal of accelerating top and bottom-line growth through targeted innovation by enhancing data management and accessibility, leading to more informed decision-making.
• The activities involved in this project include:
  • Creating a database and input interface to record additional properties related to an SKU such as manufacturing country, BBN, end use, % recycled content if PET, and process line.
  • Analysing NSR weekly/monthly data to automatically tag an SKU as active or inactive and define its seasonality based on recorded sales data.
  • Analysing current IP data and applying machine learning to auto-determine the process line.
  • Combining the results from the first 3 activities to create an SKU data master.
  • Rebuilding existing supply chain tools using the new SKU data master as standard data source for SKU properties.
• The benefit of this project includes:
  • Efficiency Improvement: Eliminate the use of multiple data source files which requires manual manipulation.
  • Data Consolidation: Creation of a single source of SKU information that can be used in multiple reports and tools.
  • Enhanced Portfolio Analysis: Provide additional context in portfolio analysis for scoping and screening.

Key Responsibilities:

• Engage with the supply chain team and related functions to understand business needs and identify opportunities to integrate data science solutions for data-driven solutions.
• Deliver defined internal supply chain digitalization project aimed to improve efficiency and effectiveness of supply chain processes.
  • Develop scalable data pipelines for analytical and operational use cases.
  • Design and implementation of AI/ML models to optimize supply chain processes, as per defined use case.
  • Contribute to the creation of a unified data model to enable exponential scalability and enterprise value creation.
  • Help automate decisions in existing processes through intelligent automation and RPA technology.
  • Document and communicate findings and insights to stakeholders at all levels.

Qualifications:

• Currently pursuing a post-graduate degree in Computer Science, Data Science, Engineering, or a related field.
• Strong analytical skills with experience in SQL, Python, R, or similar data analysis tools.
• Familiarity with machine learning frameworks and libraries.
• Excellent problem-solving abilities and a 'problem first, not data first' approach.
• Ability to work collaboratively in a team environment.
• Strong communication skills to effectively share insights and recommendations.

Learning Opportunities:

• Gain hands-on experience with real-world supply chain challenges and data science applications.
• Work closely with experienced supply chain professionals and data scientists.
• Contribute to impactful projects that drive operational efficiency and innovation.
• Develop a deep understanding of the supply chain domain and the role of data in decision-making processes.