Associate Director, Distribution Analytics—Cell Therapy

At AstraZeneca Cell Therapy, we are building a patient-centered and globally scalable supply chain to support the delivery of innovative cell therapies. As our portfolio and distribution network expand, data, advanced analytics, and artificial intelligence will be critical to improving visibility, anticipating risks, optimizing decisions, and ensuring reliable delivery to patients and clinical sites.

The Associate Director, Distribution Analytics – Cell Therapy will lead the use of data, analytics, and AI-enabled decision support to improve delivery performance across the Cell Therapy distribution network. This role will create the insights, predictive capabilities, and analytical tools needed to anticipate risks, optimize inventory and logistics decisions, and protect reliable patient supply.

The Associate Director will establish the distribution analytics strategy, performance-management framework, dashboards, predictive tools, and data-governance practices required to support clinical and future commercial operations. You will partner closely with Patient Supply Operations, Clinical Supply, Global Supply Chain, Manufacturing, Quality, Regulatory, Finance, Procurement, Digital, Commercial Operations, and external logistics providers.

You will translate complex operational data into clear business actions and measurable improvements in delivery reliability, inventory performance, cost, compliance, and supply chain resilience. AI solutions will be developed with appropriate human oversight, transparency, data-quality controls, and alignment with AstraZeneca policies and applicable regulatory requirements.

What You'll Do

• Develop and execute the distribution analytics and AI strategy across the Cell Therapy network, including data products, dashboards, predictive models, performance metrics, and governance routines.
• Partner with the Director, Cell Therapy Delivery Performance, to establish a consistent framework for measuring and improving delivery performance across internal operations and external logistics providers.
• Own analytics across the distribution lifecycle, including demand signals, order management, inventory positioning, shipment planning, carrier performance, depot operations, delivery confirmation, and exception management.
• Define and maintain key performance indicators covering delivery reliability, order cycle time, on-time-in-full performance, inventory availability, shipment lead times, temperature excursions, customs delays, cost, and exception resolution.
• Develop predictive and AI-enabled analytics to identify potential shipment delays, inventory shortages, capacity constraints, temperature excursions, and other risks that may affect patient supply or manufacturing continuity.
• Translate data and AI-enabled insights into clear recommendations and operational decisions for senior stakeholders, program teams, operational teams, and external service providers.
• Support clinical supply planning, study startup, site activation, enrollment forecasting, inventory replenishment, and delivery performance across programs and geographies.
• Partner with Digital and IT to develop data models, system integrations, reporting solutions, analytics platforms, and AI-enabled tools, including solutions connected to SAP and other supply chain systems.
• Establish data-quality controls and master-data standards for product, site, depot, lane, carrier, shipment, order, inventory, temperature, and delivery-event data.
• Lead root-cause analysis and performance improvement for distribution issues, including missed deliveries, shipment deviations, inventory shortages, temperature excursions, customs holds, and logistics-provider concerns.
• Develop analytics to support logistics-provider scorecards, cost-to-serve analysis, network optimization, business continuity, and distribution-risk management.
• Promote the responsible use of AI by ensuring appropriate documentation, human oversight, model monitoring, data governance, and escalation of limitations or uncertainties.
• Drive adoption of analytics products by understanding user needs, simplifying decision workflows, measuring utilization, and continuously improving tools based on stakeholder feedback.
• Lead change management for new analytics, reporting, and AI-enabled operating practices, ensuring insights are embedded into routine decision-making.
• Build and develop a high-performing distribution analytics capability, including team leadership, role clarity, prioritization, coaching, and development. Where the organization is initially matrixed, lead cross-functional analytics workstreams and establish the capabilities required to scale the team.
• Present performance trends, risks, insights, and recommendations to senior leadership and relevant governance forums.

Essential Skills and Experience

• Bachelor's degree in Data Analytics, Supply Chain, Engineering, Computer Science, Statistics, Business Administration, Life Sciences, or a related field.

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