Cell Therapy Manufacturing Planning Lead

AstraZeneca•Los Angeles, CA

7d•Hybrid

About The Position

Are you ready to convert complex manufacturing realities into clear choices that expand patient access to breakthrough cell therapies? Do you thrive at the point where analytics, operations and investment decisions converge to shape how life-changing medicines reach people who need them? In this role, you will be the enterprise’s cell therapy manufacturing planning authority—translating site-level intelligence into standardized assumptions, scenario models and network recommendations that inform our most important supply decisions. Your work will directly influence how and where we manufacture, how quickly we scale, and how we balance risk and cost—accelerating therapies for patients facing cancer and other serious diseases. Reporting to the Head of Cell Therapy Manufacturing and partnering closely with Global Supply Chain, Finance and site leaders, you will build the analytical backbone that guides capacity, technology transitions and capital deployment across our network. This is a high-visibility opportunity to shape a next-generation supply network and deliver tangible impact at speed.

Requirements

Bachelor’s degree in supply chain Analytics, Operations Research, Engineering, Applied Mathematics, Data Science, or related quantitative field
Minimum 10 years in pharmaceutical/biotech supply chain analytics, network modeling, or strategic planning with at least 5 years focused on network-level scenario planning or capacity optimization
Experience with cell therapy, biologics, or personalized medicine supply chains strongly preferred
Advanced proficiency in capacity modeling, Monte Carlo simulation, optimization algorithms, and multi-variable scenario analysis; understanding of cell therapy manufacturing constraints; familiarity with supply chain governance processes from a contributor/input-provider perspective
Expert-level proficiency in advanced analytics platforms (Python, R, or equivalent), capacity modeling tools, simulation software, and data visualization (Power BI, Tableau); experience with planning platforms (Kinaxis, o9, OMP from a data-input and requirements-definition perspective
Exceptional quantitative analysis, structured problem-solving, storytelling with data, ability to synthesize complex multi-source inputs into clear recommendations, collaborative partnering mindset, comfort operating within established governance frameworks while influencing outcomes through analytical rigor
Intellectually curious, detail-oriented yet able to communicate at the executive level, comfortable with ambiguity, and adept at building credibility through the quality of analytical outputs rather than positional authority.

Nice To Haves

Master's degree
Hands-on experience with cell therapy or personalized medicine manufacturing, including understanding of vein-to-the-vein constraints and variable cycle times
Working knowledge of cGMP operations and the practical realities of tech transfer, validation and change control
Proven track record designing or operating digital twins and advanced planning solutions for complex, multi-site networks
Experience building investment cases for manufacturing capacity and technology transitions, including sensitivity analyses and trigger-based phasing
Demonstrated capability to lead cross-functional data collection and validation processes across sites and functions
Advanced cost modeling expertise, including labor modeling, overhead absorption, and make/buy or internal/external network scenarios
Exposure to robotics, closed systems and automation roadmaps in a regulated manufacturing environment
Strong executive communication, including simplifying complex scenarios into option-value trade-offs for senior governance forums

Responsibilities

Synthesize inputs from site heads and site supply chain leads into a clear, maintained set of planning assumptions; recommend capacity allocations, geographic footprint, and risk-balanced configurations that protect supply and enable growth.
Build and maintain sophisticated models that test demand variability, technology transitions, new product introductions, workforce constraints and capital sequencing; turn outputs into actionable choices for Cell Therapy Technical Operations and structured inputs for Global Supply Chain Network Planning.
Develop multi-parameter capacity models incorporating cycle times, technology readiness, workforce availability and maintenance schedules; optimize across COGM, workforce utilization and adoption pacing to unlock step-change performance.
Partner with Finance and site operations to model COGM across the network; identify supply configurations and investment strategies that deliver advantaged unit economics at multiple demand levels.
Quantify headcount, skill-mix evolution, training lead times and labor cost sensitivity for key scenarios; ensure strategies are executable and aligned with the Workforce Evolution roadmap.
Model automation, closed systems, next-generation platforms and robotics transitions; define parallel processing, revalidation timelines and expected productivity gains to de-risk changeovers.
Establish structured processes to collect, validate and normalize operational data and forward-looking assumptions from sites; maintain high data integrity for planning and governance use.
Participate in Global Supply Chain governance with CTM-specific data packages, feasibility assessments and scenario outputs; influence outcomes with rigorous analysis within established frameworks.
Collaborate with Global Supply Chain and Portfolio teams to interpret patient demand signals, launch timelines and indication expansions; translate these into capacity requirements and site-level constraints.
Build scenario-backed business cases for network investments; recommend sequencing, capacity triggers and phased options that protect patients and capital efficiency.
Quantify supply risks across the network; model mitigations and present risk-adjusted recommendations to guide resilient decision-making.
Define CTM-specific requirements for digital twins, AI-enabled demand sensing and capacity optimization algorithms; partner to configure tools that reflect cell therapy realities.
Develop and report CTM network metrics such as capacity utilization, on-time-in-full, schedule adherence and COGM reduction progress; spotlight insights that drive continuous improvement.