Executive Director, Enterprise Process & Innovation

Purpose 

• Drive end-to-end process transformation across the value chain - spanning Operations, Manufacturing, Supply Chain, and Commercial - by embedding AI at the point of work to improve quality, service, speed, cost, and patient impact.  

• Shift the enterprise from function-centric workflows to decision-centric operating models that eliminate bottlenecks and reduce manual handoffs, with a particular focus on high-value decisions in manufacturing execution, quality, planning, procurement, field engagement, and revenue growth. 

Accountabilities 

• Redesign critical end-to-end processes with a value-chain lens. Focus on decision-centric models that integrate AI into daily work across Manufacturing (e.g., shop-floor decision support, batch release, deviation triage), Operations/Supply Chain (e.g., demand/supply planning, inventory optimization, logistics), and Commercial (e.g., next-best action, customer engagement, pricing/contracting). Remove structural bottlenecks and reduce decision latency to deliver measurable business outcomes. 

• Act as a cross-functional integrator to incubate and scale AI-enabled use cases across Operations, Manufacturing, Quality, Supply Chain, Commercial, Medical, Legal, Finance, and Procurement. Establish repeatable pathways to move from pilot to scaled enterprise capabilities with proven impact on service levels, cycle time, yield, and revenue. 

• Advisory role and value realization: Partner with senior leaders in Operations, Manufacturing, and Commercial to frame problem statements, quantify benefits, and align AI solutions to outcomes such as OEE, throughput, COGS, right-first-time, forecast accuracy, customer engagement effectiveness, and growth. Collaborate with Finance to define value metrics, track benefits realization and ROI, and ensure sustained impact. Advise where AI shifts operating leverage versus where traditional optimization suffices.

• AI operating model and governance: Collaborate with Enterprise AI, Data, IT, Risk, Quality, Legal/Compliance, and GBS to ensure solutions are scalable, secure, compliant, and ethical - fit for regulated manufacturing and GxP environments, data privacy in Commercial, and enterprise-grade risk controls. Codify pragmatic governance that accelerates delivery without compromising safety or trust. 

• Change leadership and capability building: Lead adoption through new ways of working, role redesign, and clear decision rights - across plant operations, global supply chain, and field/commercial teams. Build enterprise understanding of AI’s role in process transformation through executive storytelling and hands-on engagement on the shop floor and with go-to-market teams. Develop talent and communities of practice in process innovation, AI product thinking, and systems design; plan for succession. 

• Delivery and scale: Lead or coordinate complex, high-value, AI-enabled improvement initiatives from idea to pilot to scaled capability. Orchestrate cross-functional squads to remove blockers and embed AI into routine operations (e.g., eBR/eDHR enhancements, CPV analytics, quality signal detection, S&OP/IBP decision support, territory/customer orchestration). Socialize strategic outcomes demonstrating cost, quality, service, and financial improvements. 

Essential Skills/Experience 

• Proven leadership in redesigning end-to-end processes across Operations, Supply Chain, Manufacturing, and Commercial environments, transitioning from function-optimized workflows to AI-enabled, decision-focused operating models. Demonstrated ability to identify and remove bottlenecks, manual handoffs, and slow decision points - and to build intelligence into workflows rather than layering tools. 

• Strong integrator who connects business, technology, data, and change capabilities to deliver enterprise innovation - incubating and expanding AI use cases in R&D, Manufacturing/Quality, Supply Chain, Commercial, Medical, Legal, Finance, and Procurement - with repeatable methods to progress from pilot to scaled capability. 

• Internal consultancy and value realization experience with executive stakeholders in Operations, Manufacturing, and Commercial: shaping problem statements; building value cases tied to OEE, yield, cycle time, scrap/rework, forecast accuracy, service levels, and revenue growth; partnering with Finance to define metrics, track benefits and ROI, and secure sustained impact; advising where AI changes operating leverage. 

• AI operating model and governance: Experience partnering with Enterprise AI, Data, IT, Risk, Quality, Legal/Compliance, and GBS to deploy responsible AI in regulated environments—GxP manufacturing and quality, as well as compliant Commercial use cases - balancing speed with safety and trust.

• Change leadership and capability building in operational and commercial contexts: driving adoption with new ways of working and decision accountability across plants, supply chain functions, and field forces; educating senior leaders; building talent and communities of practice in process innovation, AI product thinking, and architectural planning; thoughtful succession planning. 

• Delivery and scale: Track record orchestrating cross-functional squads to embed AI into day-to-day operations (e.g., predictive maintenance, batch release prioritization, quality trending and signal detection, IBP/S&OP decision support, next-best engagement, omnichannel optimization) and communicating benefits across cost, quality, service, and growth dimensions to evidence ROI. 

• Executive-level advisory experience translating ambiguous operational and commercial challenges into clear value cases and operating leverage, with a consistent record of delivering line-of-business impact. 

• Expertise in decision-centric operating models, process engineering, and systems design; familiarity with Lean, Six Sigma, TPM, and digital/advanced manufacturing methods (e.g., CPV, eBR, PAT) as well as Commercial excellence practices (e.g., segmentation, targeting, incentive comp, payer/access strategy). 

• Proficiency in AI product thinking, ML engineering and MLOps, large language models and orchestration, and data platform integration—applied to use cases such as maintenance and yield optimization, deviation/root cause acceleration, quality analytics, demand forecasting, supply planning, and omnichannel/customer engagement. 

• Experience establishing and operating governance for secure, responsible AI in regulated manufacturing and compliant Commercial settings, in partnership with risk, quality, and legal/compliance.

• Strong storytelling and education skills to engage senior operations and commercial leaders and mobilize multidisciplinary teams; demonstrated succession planning and talent development. 

• Ability to orchestrate cross-functional squads and deliver from idea to pilot to scaled capability with measurable improvements in OEE, cycle time, cost-to-serve, service levels, and revenue growth. 

Bachelor's degree required, advanced degree preferred. 

Why AstraZeneca:   

Here, your leadership directly influences how quickly and reliably we deliver therapies to patients. You will work at the intersection of cutting-edge science and advanced digital technologies, shaping early-stage approaches and turning uncertainty into pragmatic, scalable solutions. We bring unexpected teams together to unleash bold thinking, valuing kindness alongside ambition, and empower you to build partnerships and ecosystems that create new ways of working. With the investment and autonomy to succeed, you will drive cross-company change at pace, learn fast, and see the impact of your decisions across the enterprise.   

Call to Action:   

Bring your leadership to rewire our enterprise and turn AI into everyday operating leverage—step forward and shape how life-changing medicines reach patients faster.   

The annual base pay for this position ranges from $249,618.40 - 374,427.60 USD Annual. Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.   

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