Associate Director, Distribution Analytics—Cell Therapy

AstraZeneca•Gaithersburg, MD

7d•$155,517 - $233,275•Hybrid

About The Position

The Associate Director, Distribution Analytics – Cell Therapy will lead the use of data, analytics, and AI-enabled decision support to improve delivery performance across AstraZeneca’s Cell Therapy distribution network. The role establishes the distribution analytics strategy, performance-management framework, dashboards, predictive tools, and data-governance practices supporting clinical and future commercial operations. It works closely with Patient Supply Operations, Clinical Supply, Global Supply Chain, Manufacturing, Quality, Regulatory, Finance, Procurement, Digital, Commercial Operations, and external logistics providers. The role translates complex operational data into business actions and measurable improvements in delivery reliability, inventory performance, cost, compliance, and supply chain resilience. AI solutions must include appropriate human oversight, transparency, data-quality controls, and alignment with company policies and applicable regulatory requirements. The Associate Director also builds and develops the distribution analytics capability, leading teams or cross-functional workstreams and presenting insights and recommendations to senior leadership and governance forums.

Requirements

Bachelor’s degree in Data Analytics, Supply Chain, Engineering, Computer Science, Statistics, Business Administration, Life Sciences, or a related field.
At least 8 years of experience in supply chain analytics, distribution analytics, logistics, business intelligence, data science, or a related discipline.
Experience developing analytics strategies, operational dashboards, KPIs, predictive models, or decision-support tools for global supply chain or distribution operations.
Experience identifying and implementing practical AI or machine-learning use cases in supply chain, logistics, operations, or a comparable business environment.
Understanding of pharmaceutical, biologics, clinical supply, or other regulated distribution environments, including temperature-controlled logistics and third-party logistics operations.
Proficiency with business-intelligence and analytical tools such as Power BI, Tableau, SQL, Python, R, Excel, or comparable technologies, and ability to work with complex datasets.
Experience partnering with Digital, IT, data engineering, and business stakeholders to develop scalable data, reporting, and analytics solutions.
Experience leading teams, projects, or cross-functional workstreams and driving adoption of new tools and ways of working.
Strong communication, influencing, and stakeholder-management skills, including the ability to translate complex analysis and AI-enabled insights into clear business actions and measurable operational improvements.

Nice To Haves

Advanced degree in Analytics, Supply Chain, Data Science, Engineering, Business, or a related discipline.
Experience supporting cell therapy, gene therapy, ATMPs, biologics, vaccines, or other specialized pharmaceutical products.
Experience with clinical supply distribution, cryogenic or ultra-cold-chain logistics, or time-critical delivery operations.
Experience with predictive analytics, machine learning, generative AI, optimization, digital twins, or advanced scenario planning.
Knowledge of GxP, GDP, ICH-GCP, FDA, EMA, data governance, and responsible AI principles relevant to pharmaceutical and clinical supply operations.
Experience with control towers, shipment-visibility platforms, SAP, transportation-management systems, order-management systems, or comparable supply chain technologies.

Responsibilities

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 KPIs for 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 shipment delays, inventory shortages, capacity constraints, temperature excursions, and other risks to patient supply or manufacturing continuity.
Translate data and AI-enabled insights into 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 responsible AI through 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 improving tools based on stakeholder feedback.
Lead change management for new analytics, reporting, and AI-enabled operating practices, embedding insights into routine decision-making.
Build and develop a high-performing distribution analytics capability through team leadership, role clarity, prioritization, coaching, and development; lead cross-functional analytics workstreams and establish capabilities to scale a matrixed organization.
Present performance trends, risks, insights, and recommendations to senior leadership and relevant governance forums.