Lead enterprise strategy and implementation of Digital Twin and Intelligent Manufacturing capabilities across AstraZeneca’s Global Technical Operations.
Compensation
The annual base pay for this position ranges from $161,252.80 - $241,879.20 . Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Define and maintain enterprise strategy for Digital Twins, Process Twins, Process Intelligence, Modeling, Simulation, and Intelligent Manufacturing across GTO
Establish and evolve multi-year capability roadmap aligned with GTO priorities
Identify strategic opportunities to improve technology transfer, process characterization, and manufacturing readiness
Develop capability maturity models, adoption frameworks, and value realization approaches
Translate business needs into actionable capability roadmaps, standards, and implementation approaches
Lead enterprise strategy and technology direction for Digital Twin and Intelligent Manufacturing capabilities across Global Technical Operations.
Compensation
The annual base pay for this position ranges from $161,252.80 - $241,879.20 . Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Define and maintain the enterprise strategy for Digital Twins, Process Twins, Process Intelligence, Modeling, Simulation, and Intelligent Manufacturing capabilities across GTO.
Establish and evolve a multi-year capability roadmap aligned with GTO priorities, Digital Tech Transfer strategy, manufacturing modernization initiatives, and enterprise digital objectives.
Identify strategic opportunities to improve technology transfer, process characterization, scale-up, manufacturing readiness, process robustness, operational performance, and business value.
Develop capability maturity models, adoption frameworks, and value realization approaches to support enterprise scaling.
Translate business needs and manufacturing challenges into actionable capability roadmaps, standards, investment priorities, and implementation approaches.
Requirements
Master’s or PhD in Engineering, Manufacturing Systems, Chemical Engineering, Bioprocess Engineering, Data Science, Computer Science, Applied Mathematics, Operations Research, Life Sciences, or a related technical discipline.
Nice to have: Biologics manufacturing experience
Nice to have: Process development
Nice to have: Technology transfer
Nice to have: Familiarity with BaseTwo, M-Star, FlexSim, BioSolve, Solvace, AspenTech, AVEVA
