Senior Analyst, Planning Intelligence & Enablement

This is a hands‑on, high‑impact position within an intricate, fast‑paced cell therapy supply chain. You will partner with planning, procurement, manufacturing, finance, quality, master data, and digital teams to ensure trusted planning outputs today—and to design the data structures, decision logic, and guardrails that enable AI‑orchestrated, human‑governed planning in the near future. Can you see yourself turning data, parameters, and process subject area into stable, actionable plans that scale with innovation? Accountabilities SAP Planning Governance: Ensure SAP data, planning parameters, and transaction execution consistently produce reliable material requirements and supply signals. Planning Signal Health Monitoring: Track and strengthen signal quality across demand, supply, inventory, and procurement so planning outputs remain stable, accurate, and actionable. Data Integrity and Issue Resolution: Identify, investigate, and resolve data and transaction issues that distort material planning or downstream execution. Metrics and Audit Routines: Build dashboards, KPIs, and audit checks to measure planning signal strength, data quality, transaction compliance, and overall supply chain health. Decision‑Ready Analysis: Deliver clear, concise insights for S&OE, S&OP, and Tier forums, surfacing risks, weak signals, data issues, trends, and improvement opportunities. Decision‑Centric Process Mapping: Document decisions, inputs, and logic embedded in current planning workflows to create the blueprint for future AI‑enabled planning. Data Governance and AI Readiness: Support master and transactional data governance for operational execution and planning performance; define standards for data quality, structure, completeness, and context that enable high‑confidence, autonomous planning over time. Expert Planning Tools Enablement: Serve as an authority translating planning logic, SAP transactions, and master data settings into decision rules that future AI agents must replicate or improve. Exception Management Frameworks: Establish criteria for when AI‑generated plans require human review, issue, or override, with special focus on GxP‑critical materials and patient‑specific supply chains. AI‑Assisted Workflow Pilots: Test AI recommendations against current planning outputs, measure accuracy, identify gaps, and debrief to improve AI agent performance. Convert institutional planning know‑how into organized, portable formats. These include decision trees, logic maps, and exception catalogues. They can be embedded into AI systems and safeguarded as automation scales. Essential Skills/Experience Strong proficiency in SAP and understanding of supply chain transactions, core data, and planning‑relevant data structures. Proficient knowledge in Microsoft Excel, including data analysis, reconciliation, and visualization. Experience analyzing data integrity, transaction accuracy, and process compliance within supply chain systems. Good understanding of end‑to‑end supply chain processes, including material planning, purchasing, inventory management, and production execution. Ability to perform root cause analysis and translate findings into practical business actions. Good interpersonal and teamwork skills to work across planning, procurement, manufacturing, finance, and master data teams. Excellent oral and written communication skills, with the skill to communicate complex findings clearly to collaborators. Understanding of business implications of system and process issues on supply continuity, inventory, and operational performance. Knowledge of cGMP manufacturing and regulatory/compliance requirements for cell therapy and the pharmaceutical industry. 6+ years with BS/BA in related field, or 4+ years with MS/MA or MBA in related field. Desirable Skills/Exp experience Experience with SAP transaction auditing, controls, or data governance. Highly knowledgeable with Power BI, Tableau, Power Query, Power Pivot, or similar analytics tools. Expert experience with planning systems such as OMP. ERP implementation, enhancement, or scaling experience. Experience in pharmaceutical, biotech, or operations related to cell therapy product logistics. Knowledge of Python or VBA for automation and analysis. Professional certifications such as CPIM or ASCM/APICS. Curiosity and interest in understanding how AI/ML models consume and interpret planning data. Eagerness to learn and collaborate with AI tools, digital agents, and automation platforms. Ability to articulate planning logic and decision rules in structured, transferable formats. Comfort with ambiguity and evolving role scope as AI capabilities mature. Why AstraZeneca Here, supply chain is where science meets execution to reach patients at speed. You will join a diverse, agile team that applies current technology and disciplined, Lean ways of working to intricate, real‑world challenges. Expect to sit alongside manufacturing, quality, finance, and digital specialists—unexpected teams in the same room—turning data into decisive action. We value kindness alongside ambition, and we back ambitious thinking with the tools and support needed to make it real. With a pipeline of new therapies and an environment that prizes continuous improvement, your work will directly shape how life‑changing medicines move from our sites to those who need them most. Step into this role to strengthen today’s planning signals and help architect AI‑enabled decisions that keep critical therapies flowing—make your impact now! Date Posted: 26-Jun-2026 Closing Date: 02-Jul-2026 Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form. #J-18808-Ljbffr AstraZeneca GmbH