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QA Senior Specialist – Digital Lean Lead

Location Philadelphia, Pennsylvania, United States Job ID R-227463 Date posted 22/05/2025

As a Digital Lean Lead at AstraZeneca, you'll be instrumental in integrating ground breaking digital technologies to elevate our quality processes and compliance standards. Your role will involve designing and implementing digital solutions to solve business challenges, streamlining operations with lean principles, and ensuring regulatory compliance.

Accountabilities:
• Develop and implement digital strategies to address complicated business problems within the quality assurance domain.
• Use Lean manufacturing knowledge to identify and eliminate inefficiencies within quality processes.
• Lead projects to integrate innovative AI technologies, improving data analysis and predictive capabilities for quality improvement.
• Apply Six Sigma methodologies to drive operational excellence and ensure consistent quality outcomes.
• Collaborate with cross-functional teams to align digital solutions with business goals, ensuring flawless integration and sustainability.
• Supervise and evaluate the efficiency of digital initiatives, continuously seeking opportunities for improvement and best practices.
• Drive a culture of continuous improvement and learning within the Quality team through innovative digital tools and Lean Six Sigma practices.

Essential Skills/Experience:
• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• 3-5 years of experience in pharma or medical device manufacturing.
• Demonstrated experience in digital solution development and quality improvement, preferably in pharmaceutical or healthcare industry.
• Continuous learning mentality with a passion for technology and innovation.
• Proficiency in coding languages such as Python, R, or Java.
• Strong understanding of AI development frameworks and tools (e.g., TensorFlow, PyTorch).
• Familiarity with data visualization tools (e.g., Tableau, Power BI) for actionable insights.
• Knowledge of regulatory requirements and standards in the pharmaceutical industry.
• Expertise and experience in Lean Manufacturing principles.
• Excellent communication skills with the ability to translate complex technical concepts into business language.
• Proven leadership and project management skills with experience in leading cross-functional teams.
• Strong problem-solving abilities and strategic thinking.

Desirable Skills/Experience:
• Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• Experience in developing and deploying machine learning models.
• Six Sigma Certification (Green or Black Belt).

At AstraZeneca, we are driven by a dedication to excellence, constantly seeking ways to contribute through science and evidence. Our proactive approach empowers us to innovate continuously, ensuring improved outcomes for patients. We foster an inclusive community where collaboration is key, allowing us to deliver medicines sustainably and safely. With a focus on growth and innovation, AstraZeneca offers a dynamic environment where your contributions make a real difference.

Ready to make an impact? Apply now to join our team and be part of our journey towards excellence!

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

10000469 D PRGE Operations

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Glassdoor logo Rated four stars on Glassdoor

Great culture, great work assignments, supportive management. Rotation opportunity within the company. They value inclusion and diversity.