Wait, What Do You Do?

Main Duties/Responsibilities: Data Capture & Integrity Management <ul> <li>Source Data Collection: Responsible for the daily collection of raw operational data from the production floor, including machine uptime, labor hours, and output volumes.</li> <li>Data Auditing: Perform regular "sanity checks" and audits on captured data to ensure absolute accuracy before it is used for planning or reporting.</li> <li>Inventory Tracking: Capture and maintain real-time data regarding raw materials, work-in-progress (WIP), and finished goods to prevent shortages and excess.</li> </ul> Dashboard Development & Visualisation <ul> <li>Performance Visualisation: Build, update, and maintain functional dashboards (using Excel or Power BI) that track key metrics.</li> <li>Stakeholder Reporting: Prepare clear visual reports for production meetings, helping stakeholders quickly identify trends and operational bottlenecks.</li> <li>Automation of Reporting: Streamline existing manual reporting processes to ensure data is updated with minimal delay.</li> </ul> Capacity & Resource Planning Support <ul> <li>Production Scheduling Support: Work closely with the Master Production Scheduler (MPS) to align daily production schedules with available labor and machine capacity.</li> <li>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.</li> <li>Resource Allocation: Monitor resource constraints and provide data-backed recommendations on how to best distribute personnel and equipment to meet targets.</li> </ul> Daily Operational Problem Solving <ul> <li>Bottleneck Identification: Use data captured from the floor to pinpoint specific areas where production is slowing down and propose immediate solutions.</li> <li>Cross-Functional Collaboration: Act as the "data bridge" between the planning office and the production floor, ensuring communication is based on accurate facts.</li> </ul> AI & Automation: <ul> <li>Process Mapping: Document current manual planning workflows to identify candidates for AI-driven automation.</li> <li>Continuous Learning: Proactively up-skill in AI tools and frameworks to transition traditional planning into "intelligent" planning.</li> </ul> AI Integration: <ul> <li>Lead and Assist in the deployment of intelligent AI agents designed to automate routine data entry and predictive scheduling.</li> <li>Train internal stakeholders to use AI agents and provide support in challenges and issues.</li> </ul> Essential And Desirable Skills: Essential Skills <ul> <li>Education: A recently completed Bachelor’s/ master’s degree in supply chain management, Industrial Engineering, Business Analytics, or a related quantitative field.</li> <li>Advanced Data Manipulation: High proficiency in Microsoft Excel, including the use of advanced formulas (XLOOKUP, Index/Match), PivotTables, and Power Query for data cleansing.</li> <li>AI & Automation Interest: Familiarity with the concept of AI agents and how they can be applied to supply chain efficiency.</li> <li>Data Visualisation: Proven ability to build and manage functional dashboards (Excel or Power BI) that translate raw data into clear operational insights.</li> <li>Data Accuracy & Auditing: A meticulous approach to data capture, with the ability to identify discrepancies and ensure high integrity in inventory and production records.</li> <li>Analytical Thinking: Strong competency in capacity planning and resource management logic (balancing labor, machinery, and time constraints).</li> <li>Collaborative Problem-Solving: Ability to work effectively on a fast-paced production floor and communicate clearly with the Master Production Scheduler and other stakeholders.</li> <li>Innate Curiosity: A proactive "investigative" mindset with a strong desire to understand the root causes of operational challenges.</li> </ul> Desirable Skills <ul> <li>Programming Foundations: Basic knowledge of Python or SQL, or a demonstrated interest in learning these to automate manual data tasks.</li> <li>Process Mapping: Experience in documenting workflows and identifying "friction points" that are suitable for automation.</li> <li>Inventory Modelling: Previous exposure to inventory optimisation techniques (e.g., Safety Stock calculations or EOQ modelling) during academic projects or internships.</li> <li>Lean/Six Sigma: Foundational understanding of Lean manufacturing principles to help minimise waste in the production area.</li> </ul> Qualifications or Relevant Work Experience: Recently completed Bachelor’s/ Master’s degree (or equivalent) in one of the following. <ul> <li>Supply Chain Management / Logistics</li> <li>Industrial or Systems Engineering</li> <li>Business Analytics / Data Science</li> </ul> Desirable Experience: <ul> <li>Internship/ Experience: Any previous experience, internship or placement within a manufacturing, production, or logistics environment.</li> <li>Programming: Basic exposure to SQL or Python, specifically for the purpose of automating repetitive data tasks.</li> <li>Production Floor Familiarity: Comfort working in a "boots-on-the-ground" production environment and interacting directly with shop-floo</li> </ul>

Graduate Planning & Data Analyst (Leicester, LEC, GB, LE49JD)