Director, Digital Twin & Intelligent Manufacturing Capabilities
AstraZeneca is hiring a Director, Digital Twin & Intelligent Manufacturing Capabilities. It pays $161k-$242k a year and Level rates it ; you can apply on AstraZeneca.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include digital twin, intelligent manufacturing and process intelligence.
- Level classifies it as an executive role.
- Level lists 1,400+ other open roles at AstraZeneca.
- The role was posted within the past week.
AI in this role
Define and advance enterprise strategy for Digital Twins, Process Intelligence, and AI-driven manufacturing capabilities across global operations.غر
Position Summary
The Director, Digital Twin & Intelligent Manufacturing Capabilities is responsible for defining and advancing the enterprise strategy, technology direction, governance, standards, and capability roadmap for Digital Twins, Process Twins, Process Intelligence, Modeling, Simulation, Automation-enabled Manufacturing, and AI-driven manufacturing capabilities across Global Technical Operations (GTO). This role serves as GTO's enterprise leader for Digital Twin and Process Intelligence capabilities and is accountable for shaping how manufacturing science, process knowledge, automation, data, advanced analytics, artificial intelligence, and digital technologies are leveraged to improve technology transfer, process understanding, manufacturing readiness, operational performance, and business outcomes across the product lifecycle.
The Director will partner closely with MPAS, Tech Transfer, BPD, Singapore manufacturing and digital organizations, Alexion, FMC, Regional Digital Leads, Manufacturing, IT, Enterprise Architecture, Data & AI, Automation, and Site Digital teams to establish enterprise-scale capabilities and implementation frameworks that can be deployed consistently across the manufacturing network. While Regional Digital Leads and site organizations retain accountability for site-level deployment and adoption, this role is responsible for defining the enterprise capability strategy, technology direction, operating model, governance, standards, and reusable assets required to scale Digital Twin and Process Intelligence capabilities across GTO.
This position requires deep expertise in Digital Twin and Intelligent Manufacturing capabilities, combined with strong technology leadership, manufacturing and process-science credibility, automation awareness, systems thinking, vendor evaluation experience, AI and advanced analytics fluency, and a proven ability to lead large-scale cross-functional transformation initiatives in complex global organizations.
Key Responsibilities
Enterprise Strategy & Capability Leadership
- 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.
Technology, Automation & Intelligent Manufacturing Leadership
- Define how Digital Twins, manufacturing systems, automation environments, process data, simulation platforms, advanced analytics, machine learning, and AI capabilities work together as part of GTO’s Intelligent Manufacturing ecosystem.
- Lead evaluation and selection of Digital Twin, Process Intelligence, Modeling, Simulation, and AI-enabled manufacturing technologies.
- Drive technology strategy and investment recommendations across platforms, tools, vendors, and strategic partnerships.
- Assess emerging technologies and industry developments to guide future capability investments and roadmap decisions.
- Partner with Enterprise Architecture, IT, Data & AI, Automation, and Digital organizations to define scalable architectures, integration approaches, and operational models.
- Establish approaches for connecting process knowledge, manufacturing systems, automation platforms, process data, simulations, and Digital Twins through effective data flows and information architectures.
- Guide build-versus-buy decisions and strategic technology direction for Digital Twin and Intelligent Manufacturing capabilities.
Process Intelligence, Modeling & Digital Twin Governance
- Establish governance frameworks, standards, methodologies, and best practices for Digital Twin and Process Intelligence capabilities across GTO.
- Define and oversee model lifecycle management approaches, including model transition, deployment, maintenance, monitoring, documentation, and retirement.
- Establish ownership models, stewardship expectations, support models, and decision-making frameworks for Digital Twin and Process Intelligence capabilities.
- Develop reusable methods, templates, and standards that enable scalability and consistency across products, sites, and manufacturing networks.
- Ensure Digital Twin and Process Intelligence initiatives are aligned to enterprise quality, regulatory, and operational expectations.
Community of Practice & Capability Development
- Establish and lead the GTO Digital Twin & Process Intelligence Community of Practice and Center of Excellence.
- Build and maintain a network of practitioners and subject matter experts across Manufacturing, MPAS, Tech Transfer, BPD, Automation, IT, Data & AI, Site Digital organizations, and Regional Digital Leads.
- Develop standards, reference architectures, implementation guidance, training materials, and best practices to support capability maturity and enterprise adoption.
- Promote innovation, knowledge sharing, and capability development across the organization.
- Sponsor and oversee Digital Twin and Process Intelligence initiatives involving interns, graduate students, and university partnerships aligned to strategic business priorities.
- Collaborate with academic institutions, innovation partners, and external research organizations to advance Digital Twin and Intelligent Manufacturing capabilities.
Enterprise Transformation & Business Partnership
- Partner closely with MPAS, Tech Transfer, BPD, Singapore manufacturing organizations, Alexion, FMC, and Manufacturing organizations to identify opportunities and shape future-state capabilities.
- Ensure Digital Twin and Process Intelligence strategies align with broader Digital Tech Transfer, Intelligent Manufacturing, and GTO transformation objectives.
- Lead complex cross-functional initiatives requiring alignment across business, scientific, manufacturing, digital, and technology organizations.
- Influence strategic decisions and drive organizational alignment without direct authority.
- Translate emerging technologies into scalable business capabilities and measurable outcomes.
External Innovation & Vendor Management
- Build and manage relationships with strategic technology vendors, industry organizations, academic partners, and innovation ecosystems.
- Lead technology assessments, proof-of-concept initiatives, capability evaluations, and vendor-selection activities.
- Monitor industry developments in Digital Twins, Process Intelligence, Manufacturing Analytics, Simulation, Artificial Intelligence, Machine Learning, and Intelligent Manufacturing.
- Guide strategic partnerships and investment decisions that strengthen GTO’s long-term Digital Twin and Process Intelligence capabilities.
Qualifications
Required
- Advanced degree (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.
- 12-20+ years of experience in pharmaceutical, biotechnology, manufacturing, engineering, automation, process development, digital transformation, or related industries.
- Demonstrated experience leading enterprise-scale Digital Twin, Process Twin, Process Intelligence, Simulation, Advanced Analytics, Artificial Intelligence, Machine Learning, or Intelligent Manufacturing initiatives.
- Strong understanding of manufacturing systems, automation environments, industrial data flows, manufacturing data ecosystems, and Intelligent Manufacturing concepts.
- Experience evaluating technology platforms, software vendors, emerging technologies, and digital capabilities.
- Demonstrated ability to develop capability roadmaps, guide technology investments, and establish enterprise governance and standards.
- Strong understanding of AI, machine learning, advanced analytics, simulation technologies, and their practical application in manufacturing and process environments.
- Demonstrated ability to lead complex, cross-functional transformation initiatives in highly matrixed organizations.
- Proven ability to influence senior scientific, manufacturing, business, and technology stakeholders without direct authority.
- Excellent executive communication, stakeholder engagement, facilitation, and leadership skills.
Preferred
- Experience in biologics manufacturing, process development, manufacturing sciences, technology transfer, or technical operations.
- Experience working across BPD, MPAS, Manufacturing, Tech Transfer, Automation, IT, Data & AI, and Enterprise Architecture organizations.
- Familiarity with Digital Twin and Process Intelligence platforms such as BaseTwo, M-Star, FlexSim, BioSolve, Solvace, AspenTech, AVEVA, or similar ecosystems.
- Experience establishing enterprise communities of practice, governance models, capability-development programs, or Centers of Excellence.
- Experience leading innovation partnerships, university collaborations, internship programs, or applied research initiatives.
When we put unexpected teams in the same room, we unleash bold thinking with the power to encourage life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
The annual base pay for this position ranges from The annual base pay (or hourly rate of compensation) 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. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.
Are you ready to bring new insights and fresh thinking to the table?
Fantastic! We have one seat available, and we hope it’s yours.
Apply today.
Date Posted
09-Nov-2026Closing Date
22-Nov-2026Our 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.
How we rate this
Director, Digital Twin & Intelligent Manufacturing Capabilities at AstraZeneca rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where digital twin was part of your work. What did you do?
- Tell me about a project where intelligent manufacturing was part of your work. What did you do?
- Tell me about a project where process intelligence was part of your work. What did you do?
- Tell me about a project where modeling was part of your work. What did you do?
- Tell me about a project where simulation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Digital Twin, Intelligent Manufacturing, Process Intelligence, Modeling, and Simulation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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