Nandina REM is creating new sources of advanced materials for manufacturing supply chains. We are an early stage company specialising in the use of deep tech and material science to recover and remanufacture critical resources, creating a rapidly developing market for low-emission circular materials such as carbon fibre composites and metals.

 

We are seeking a meticulous and tech-savvy Supply Chain Traceability Analyst to establish and maintain robust traceability systems across our manufacturing operations. You will be responsible for ensuring end-to-end visibility of our materials and products, contributing significantly to inventory control, guaranteeing data accuracy, and exploring innovative ways to leverage AI agents to strengthen our Quality Assurance and Quality Control (QA/QC) practices. This role requires a proactive individual with a strong analytical mindset and a passion for leveraging data and technology to optimize processes.

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Please note, candidates must have the legal right to work in their jurisdiction of hire. Nandina REM is unable to sponsor local work visas for this role.

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Key Responsibilities

Traceability System Development & Implementation:

• Design, implement, and manage comprehensive traceability systems to track raw materials, components, work-in-progress, and finished goods throughout the entire supply chain.

• Evaluate and select appropriate technologies and tools (e.g., RFID, barcode scanning, blockchain) to enhance traceability capabilities.

• Develop and document standard operating procedures (SOPs) for data capture, storage, and retrieval related to traceability.
   

Inventory Control & Optimization:

• Utilize traceability data to improve inventory accuracy, reduce discrepancies, and optimize inventory levels across the supply chain.

• Analyze inventory movement patterns and identify opportunities for streamlining material flow and minimizing waste.

• Collaborate with production planning and procurement teams to ensure alignment between material availability and production schedules.
   

Data Assurance & Integrity:

• Establish and maintain data quality standards for all traceability-related information.

• Implement data validation processes and conduct regular audits to ensure accuracy, completeness, and consistency of traceability records.

• Identify and resolve data integrity issues, working with relevant teams to implement corrective actions.
   

Leveraging AI Agents for QA/QC Enhancement:

• Research, evaluate, and pilot AI-powered tools and agents that can leverage traceability data to enhance QA/QC processes.

• Collaborate with the QA/QC team to identify areas where AI can improve defect detection, predict potential quality issues, and automate inspection processes based on material origin and processing history.

• Develop and implement AI-driven alerts and reporting mechanisms based on traceability data to flag potential quality risks.
   

Supply Chain Visibility & Reporting:

• Generate regular reports and dashboards on key traceability metrics, providing insights into material flow, inventory levels, and potential risks.

• Communicate traceability information effectively to internal stakeholders, including production, quality, logistics, and management teams.

• Support compliance efforts related to product origin, safety regulations, and sustainability initiatives through accurate traceability data.
   

Continuous Improvement:

• Stay updated on the latest trends and technologies in supply chain traceability and AI applications in manufacturing.

• Identify opportunities for continuous improvement in traceability processes, data management, and the integration of AI tools.
   

Skills & Experience.

• Bachelor's degree in Supply Chain Management, Logistics, Industrial Engineering, Data Science, or a related field.

• Minimum of 5 years of experience in supply chain analysis, inventory control, or traceability within a manufacturing environment.

• Demonstrated understanding of supply chain principles and best practices.

• Experience with implementing and managing traceability systems (e.g., barcode, RFID).

• Proven ability to analyze large datasets, identify trends, and generate actionable insights.

• Excellent data management and data quality assurance skills.

• Familiarity with ERP systems and warehouse management systems (WMS).

• Experience with AI/ML concepts and their potential applications in manufacturing or supply chain.

• Familiarity with data visualization tools (e.g., Tableau, LookerStudio).

• Experience with programming languages relevant to data analysis (e.g., Python, SQL).