Job Title:  Graduate Planning & Data Analyst

Main Duties/Responsibilities

 1. Data Capture & Integrity Management

     • Source Data Collection: Responsible for the daily collection of raw operational data from the production floor, including machine uptime, labor hours, and output volumes.

     • Data Auditing: Perform regular "sanity checks" and audits on captured data to ensure absolute accuracy before it is used for planning or reporting.

• Inventory Tracking: Capture and maintain real-time data regarding raw materials, work-in-progress (WIP), and finished goods to prevent shortages and excess.

2. Dashboard Development & Visualisation

• Performance Visualisation: Build, update, and maintain functional dashboards (using Excel or Power BI) that track key metrics.

     • Stakeholder Reporting: Prepare clear visual reports for production meetings, helping stakeholders quickly identify trends and operational bottlenecks.

• Automation of Reporting: Streamline existing manual reporting processes to ensure data is updated with minimal delay.

 3. Capacity & Resource Planning Support

     • Production Scheduling Support: Work closely with the Master Production Scheduler (MPS) to align daily production schedules with available labor and machine capacity.

     • Scenario Modelling: Help simulate "what-if" scenarios (e.g., the impact of a machine breakdown or an urgent order) to help the team pivot quickly.

• Resource Allocation: Monitor resource constraints and provide data-backed recommendations on how to best distribute personnel and equipment to meet targets.

  4. Daily Operational Problem Solving

     • Bottleneck Identification: Use data captured from the floor to pinpoint specific areas where production is slowing down and propose immediate solutions.

• Cross-Functional Collaboration: Act as the "data bridge" between the planning office and the production floor, ensuring communication is based on accurate facts.

 5. AI & Automation:

     • Process Mapping: Document current manual planning workflows to identify candidates for AI-driven automation.

     • Continuous Learning: Proactively up-skill in AI tools and frameworks to transition traditional planning into "intelligent" planning.

6. AI Integration:

• Lead and Assist in the deployment of intelligent AI agents designed to automate routine data entry and predictive scheduling.
• Train internal stakeholders to use AI agents and provide support in challenges and issues.

Essential And Desirable Skills

Essential Skills

     • Education: A recently completed Bachelor’s/ master’s degree in supply chain management, Industrial Engineering, Business Analytics, or a related quantitative field.

     • Advanced Data Manipulation: High proficiency in Microsoft Excel, including the use of advanced formulas (XLOOKUP, Index/Match), PivotTables, and Power Query for data cleansing.

     • AI & Automation Interest: Familiarity with the concept of AI agents and how they can be applied to supply chain efficiency.

     • Data Visualisation: Proven ability to build and manage functional dashboards (Excel or Power BI) that translate raw data into clear operational insights.

     • Data Accuracy & Auditing: A meticulous approach to data capture, with the ability to identify discrepancies and ensure high integrity in inventory and production records.

     • Analytical Thinking: Strong competency in capacity planning and resource management logic (balancing labor, machinery, and time constraints).

     • Collaborative Problem-Solving: Ability to work effectively on a fast-paced production floor and communicate clearly with the Master Production Scheduler and other stakeholders.

• Innate Curiosity: A proactive "investigative" mindset with a strong desire to understand the root causes of operational challenges.

Desirable Skills

     • Programming Foundations: Basic knowledge of Python or SQL, or a demonstrated interest in learning these to automate manual data tasks.

     • Process Mapping: Experience in documenting workflows and identifying "friction points" that are suitable for automation.

     • Inventory Modelling: Previous exposure to inventory optimisation techniques (e.g., Safety Stock calculations or EOQ modelling) during academic projects or internships.

     • Lean/Six Sigma: Foundational understanding of Lean manufacturing principles to help minimise waste in the production area.

Qualifications or Relevant Work Experience

• Recently completed Bachelor’s/ Master’s degree (or equivalent) in one of the following.

     • Supply Chain Management / Logistics

     • Industrial or Systems Engineering

     • Business Analytics / Data Science

Desirable Experience

• Internship/ Experience: Any previous experience, internship or placement within a manufacturing, production, or logistics environment.

• Programming: Basic exposure to SQL or Python, specifically for the purpose of automating repetitive data tasks.

• Production Floor Familiarity: Comfort working in a "boots-on-the-ground"       production environment and interacting directly with shop-floo