Senior Scientist, Analytical Sciences

AstraZeneca • Santa Monica, CA

1d • Onsite

About The Position

Our mission is to build fully automated analytical workflows that improve operational efficiency and help high quality cell therapies reach patients faster. We’re seeking a critical thinker and hands‑-on‑ executor who anticipates scaleup challenges and turns them into practical, automation‑ ‑ready solutions. As a Senior Scientist within Analytical Sciences, you will bridge wetlab execution, emerging lab automation, and pragmatic data practices to transform analytical workflows for engineered cell therapy. You will report to the Associate Director of Analytical Sciences and You will collaborate with the Process Sciences, Analytics, and Technology (PSAT) team and the Quality organization within Cell Therapy Development & Operations (CDTO), building internal capabilities and mentoring junior team members. You will bridge the gap between physical laboratory execution, lab automation, and data science applications. You will own key initiatives that drive operational and data automation, architecting fit-for-purpose technologies to transform analytical workflows. Partnering closely with analytical automation, operation and development scientists, you will define strategy and deliver broad analytics to support process development, product characterization, and testing methodologies for novel engineered cell therapy products. You will lead feasibility and proof of concept studies, assess new technologies, and translate proven manual methods into automation ready workflows that support process development, product characterization, and testing strategies.

Requirements

• Laboratory Automation & Analytical Domain: Experience operating and troubleshooting automated liquid handlers (e.g., Hamilton, Tecan) and integrating with common analytical modalities (e.g., flow cytometry, imaging, plate readers). Ability to translate manual SOPs into automation‑ready workflows in partnership with AA.
• Wet‑Lab and Analytical Operations: Proficiency in primary cell culture/PBMC handling, sterile technique, cell counting/viability, basic flow cytometry panel design and titration, and genomic assay fundamentals; strong QC mindset with attention to documentation and controls.
• DES and Digital Twins: Hands-on experience building and validating discrete event simulation models for lab environments using tools such as Anylogic, Simio, and ExtendSim. Ability to calibrate models with empirical data (cycle times, hold time, failure rates, changeover, resource constraints) and run scenarios analysis for capacity, scheduling and buffer design.
• Statistical Breadth: Solid foundation in experimental design (screening/optimization), regression, and multivariate analysis.
• Programming and Platforms: Proficient in Python, with strong SQL skills. Practical experience with cloud analytics (Snowflake/AWS) and data tools, prioritizing broad capability to connect lab infrastructure over deep software engineering expertise.
• Communication and Leadership: Demonstrated ability to lead cross-functional initiatives spanning physical robotics and digital infrastructure, influencing without authority, and presenting complex analyses to senior stakeholders.
• Compliance: Working knowledge of GxP environments, data integrity, and 21 CFR Part 11; experience authoring validation documentation for both software and automated lab equipment.
• B.S. in Immunology, Cell Biology, Bioengineering, Analytical Sciences, or a related scientific discipline with 5+ years of relevant hands‑on experience or M.S. in Immunology, Cell Biology, Bioengineering, Analytical Sciences, or a related scientific discipline with 3+ years of relevant experience or Ph.D. in Immunology, Cell Biology, Bioengineering, Analytical Sciences, or a related scientific discipline with no prior industry experience required.

Responsibilities

• Lab Automation & Digitalization: Partner with automation engineers to translate manual bench protocols into structured, automation ready workflows (sample maps, deck layouts, liquid classes, error‑ ‑recovery steps). Support programming, optimization, and maintenance of automated liquid handling systems (e.g., Hamilton, Tecan, BioMek, Prime) to scale high throughput‑ assays and improve robustness.
• Analytical PoC and Method Prototyping: Design and execute wetlab feasibility studies to evaluate new analytical platforms (e.g., flow cytometry, imaging, plate readers, genomic assays) and sample‑ prep devices. Develop and refine bench protocols with a QC‑ centric focus on precision, accuracy, and ruggedness; apply ‑DOElite approaches where appropriate and document with clear SOP‑-style‑ practices.
• Hybrid Technical Delivery: Lead the development of statistical solutions, data workflows and DES models (e.g., Anylogic, Simio, ExtendSim) that connect automated physical processes to analytical method development, robustness, and lifecycle management.
• Data Architecture & Traceability: Build scalable data pipelines integrating physical instrument and robotics data, LIMS/ELN, MES/historians, and cloud environments, ensuring data integrity (ALCOA+) and traceability from the deck to the database.
• Experimental Design & Analysis: Plan studies that estimate throughput and variability drivers; optimize assay steps and automated processes with appropriate controls and basic statistical analyses.
• Cross-Functional‑ Partnership: Collaborate with Operation and Quality to simulate assay and instrument schedules, align technology selection, method design with process needs and future regulatory expectations. Communicate results and recommendations to technical and nontechnical stakeholders; provide clear go/‑nogo criteria for new technologies‑.
• Instrument Onboarding & Integration: Coordinate vendor demos and side-by‑-side‑ comparisons against existing tools, capturing performance, usability, serviceability, and total cost of ownership. Summarize findings in concise evaluation reports.
• Communication: Translate scientific and operational insights into roadmaps, throughput impacts, success metrics, and investment cases that support decision-making‑ without over‑reliance on advanced modeling.
• Compliance: Support computerized system validation/assurance (CSV/CSA) for analytics tools and automated liquid handlers, incorporating 21 CFR Part 11, data integrity, and GxP considerations.
• Continuous Improvement & Safety: Uphold safety and aseptic best practices; identify opportunities to streamline workflows, reduce manual steps, improve reproducibility, and build training materials for technology adoption.

Benefits

• qualified retirement program [401(k) plan]
• paid vacation and holidays
• paid leaves
• health benefits including medical, prescription drug, dental, and vision coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees